WO2015181814A2

WO2015181814A2 - System, method and computer program product for assisted information collection

Info

Publication number: WO2015181814A2
Application number: PCT/IL2015/050512
Authority: WO
Inventors: Noam SMETANA; Amikam LEVANON; Ran Levy
Original assignee: Cidabra Technologies Ltd
Priority date: 2014-05-29
Filing date: 2015-05-14
Publication date: 2015-12-03
Also published as: IL232895A0; WO2015181814A3

Abstract

A computer-implemented method for assisted information collection, comprising executing on a processor: for a first inquisitive statement (IS) selected by a plurality of users, obtaining a selection of each of the users of a following IS out of a set of optional ISs which is selected for the user out of a plurality of second ISs associated with the first IS by a connectivity model; processing the selections of the users, to determine a connection strength evaluation (CSE) for each connection out of a plurality of connections between the first IS and a respective second IS out of the second ISs; writing the determined CSEs to the connectivity model; in response to selection of the first IS by a new user, selecting a selected set of ISs based on a plurality of CSEs out of the determined CSEs; and presenting the selected set of ISs to the new user.

Description

SYSTEM. METHOD AND COMPUTER PROGRAM PRODUCT FOR ASSISTED

INFORMATION COLLECTION

Field of the Invention

[001] The present invention is in the field of collecting and mapping information over a data network, such as the internet. The present invention further relates to methods, systems and computer program products for effectively obtaining required information from relevant sources.

Background of the Invention

[002] In the world-wide-web search engines are very well known, and used by web users all the time. Many search engines exist in the field, for example, Yahoo, Google, etc. The searching method of most of the search engines is based on semantics, such as keywords and phrases the user types in the search field, and as a result, the search engine returns links to various website pages, which contain information that may be relevant to the keywords or the phrases that were typed by the user.

[003] However, in many cases the user is unfamiliar with the subject he wants to be informed about and doesn't even know what is needed to be asked (e.g. typed as keywords or phrases into the search field of the search engine) in order to be provided with the most relevant information. In many cases, the best search phrases may not be even semantically related to the wording of the subject that the user wanted to be informed about. Even when the user is familiar with the subject, generally his knowledge is limited to few aspects only, where naturally, he may even be unaware of this limitation.

[004] Traditional search engines are therefore often insufficient, since the user either wastes time in reading many results (e.g. websites' pages) provided as the search results just to understand what the key issues of the subject are, or has to consult other people who have some knowledge in the field about the right keywords and/or phrases which are likely to lead to the best search results.

[005] If the best resource of information or solution to the issue that the user is interested in is an experienced person or an application, the search engine might not even provide a link to such resources because traditionally the digital entities of people and applications are not semantically related to all possible relevant search keywords and phrases. [006] Effective search strongly depends on using the right keywords and/or phrases typed into the search engine. In traditional search engines, however, each user must obtain these right keywords or phrases by himself. In some cases, these search engines will suggest keywords and/or phrases to the user (e.g., by autocomplete features), but still these suggestions will be based on the keywords and/or phrases that the user was already able to provide.

[007] Another traditional method of seeking information is via websites of questions and answers (Q&A). There are dedicated sites for asking questions about subjects of interest, such as medical or cooking Q&A sites, general purpose Q&A sites etc. However, to get the right answer the user needs to ask the right question, and therefore generally the user still must be familiar with the subject in order to know what to ask and have a good idea of what he is looking for. The user can ask a question in the site with the hope that somebody else will answer him, or review existing sets of questions and answers that were previously asked and answered by others. All the questions in these kinds of sites are often organized semantically or according to topics and traditionally there are no links between questions that may be relevant to the same purpose, but appear in different topics or that has no semantic relationship. Also, in many cases, these questions do not normally cover the entire scope of the required information, which typically includes many different aspects of a desired subject, and the user cannot be aware of such limitation.

[008] Another problem that users are dealing with is the organization of the data and information that are acquired from the web (or another data network or application). In most cases, if a user wants to search information on some subject and he acquired the information from several websites, he usually has to keep all website pages concurrently open, take notes manually, or either save or print the pages he found to be useful, in order to keep the information and generate a broad personal perspective of the subject. Therefore, there is a need for a method for effectively organizing the information that was collected from all the different web sites and from other data sources and making it available for reference with connection to the desired objective of the user.

[009] There is therefore a need to provide methods, systems and computer program products for information collection, which enable users to obtain relevant information with a dedicated guidance

[0010] There is further a need to provide methods, systems and computer program products of guidance for achieving desired information regarding an objective or interest, obtaining the best keywords, phrases and/or questions to ask, and the best data sources to get the desired information from. [0011] There is further a need to provide methods, systems and computer program products for effectively and intuitively organizing all the obtained information and/or questions, using a personal data structure.

[0012] Further purposes and advantages of this invention will appear as the description proceeds. General Description

[0013] According to an aspect of the invention, a computer-implemented method for assisted information collection is disclosed, the method including executing on a processor the steps of: (a) for a first inquisitive statement selected by a plurality of users, obtaining a selection of each user out of the plurality of users of a following inquisitive statement out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; wherein the set of optional inquisitive statements is selected for the user out of a plurality of second inquisitive statements associated with the first inquisitive statement by a connectivity model stored in a tangible memory module; (b) processing the selections of the plurality of users, to determine a connection strength evaluation for each connection out of a plurality of connections between the first inquisitive statement and a respective second inquisitive statement out of the plurality of second inquisitive statements; (c) writing the determined connection strength evaluations to the connectivity model; (d) in response to selection of the first inquisitive statement by a new user, selecting a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and (e) presenting the selected set of inquisitive statements to the new user.

[0014] According to a further aspect of the invention, the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

[0015] According to a further aspect of the invention, the method further includes obtaining a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and providing to the new user information associated by the connectivity model with the selected inquisitive statement.

[0016] According to a further aspect of the invention, the method further includes repeating the stages of obtaining selections, processing the selections of the plurality of users to determine connection strength evaluations and writing the connection strength evaluations to the connectivity model for one or more of the second inquisitive statements, thereby determining connection strength evaluations of different levels of connections with respect to the first inquisitive statement. [0017] According to a further aspect of the invention, the repeating is executed for multiple levels of connections, wherein the method includes repeating the selecting of a selected set of inquisitive statements for each of a series of selecting by the new user of inquisitive statements out of selected sets of inquisitive statements, thereby exposing the new user to a group of inquisitive statements which are relevant to an objective of the user as selected by selecting the first inquisitive statement.

[0018] According to a further aspect of the invention, the method further includes normalizing with respect to each other the connection strength evaluations of connections stemming from each second inquisitive statements out of the one or more second inquisitive statements.

[0019] According to a further aspect of the invention, the method includes obtaining for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; and storing the sequence of selections in a data base stored on a non-volatile memory storage.

[0020] According to a further aspect of the invention, the method further includes: analyzing the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and presenting the at least three inquisitive statements simultaneously, in response to selection of the first inquisitive statement.

[0021] According to a further aspect of the invention, the method further includes recording for at least one second inquisitive statement activities of different users which are associated with the respective second inquisitive statement, wherein the determining of the connection strength evaluation for the at least one second inquisitive statement is further based on the recorded activities.

[0022] According to a further aspect of the invention, the obtaining further includes obtaining selection related parameters associated with each of the selections of the plurality of users, wherein the processing includes processing the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the connection strength evaluation as a connection strength vector including at least two connection strength values, wherein the selecting of the selected set of inquisitive statements is based on a subset of connection strength values of each of the plurality of connection strength evaluations, the subset being selected in response to user parameters of the new user.

[0023] According to an aspect of the invention, a computer-implemented method for assisted information collection is disclsoed, including executing on a processor the steps of: for each user out of a plurality of users, obtain search history which includes information of inquisitive statements used by the user with one or more web search system over at least one search duration of the user; processing the plurality of search histories of the plurality of users, to determine connection strength evaluations for a plurality of directional connections between inquisitive statements used by the plurality of users; writing the determined connection strength evaluations to a connectivity model; based on connection strength evaluations of the connectivity model and on a search history of a new user (the search history of the new user including at least one of the inquisitive statements of the connectivity model), selecting a selected set of inquisitive statements out of the inquisitive statement of the connectivity model; and presenting the selected set of inquisitive statements to the new user.

[0024] According to an aspect of the invention, a method for providing guidance to a user of a data network for obtaining required information regarding a user defined objective is disclosed, including the steps of: (a) responsive to a request for guidance from each user out of plurality of users, the request being associated with an objective that is stored in a database, displaying to the user a list of questions/phrases and objectives that are connected to the objective and allowing the user to select questions/phrases out of the list of questions/phrases, wherein the database includes: (I) at least one user defined objective; (II) a plurality of questions/phrases of one or more words; and (III) a model of connections including connections between questions/phrases and objectives, and connections between questions/phrases and other questions/phrases; (b) storing the selections of each user and his personal navigation paths through the selected questions/phrases that lead to said selections; (c) assigning numerical strengths to each connection by aggregating information from the collection of paths of users out of the plurality of users that are associated with the same objective, in response to the popularity of usage of said connection among users; and (d) displaying questions/phrases as continuation questions/phrases of other questions/phrases, based on the assigned strengths.

[0025] According to a further aspect of the invention, the method for providing guidance further includes allowing users to add questions/phrases and objectives to the database; and generating new connections in the database based on the added questions/phrases and objectives.

[0026] According to a further aspect of the invention, the method for providing guidance further includes dynamically updating strengths to at least one connection by repeating the stages of displaying, allowing, storing and assigning.

[0027] According to a further aspect of the invention, in the method for providing guidance a connection is represented by a plurality of connection values associated with the at least one of the following parameters: (a) contextual parameters of the user; (b) geographical location of the user; (c) characterizing features of the user; and (d) physical or mental conditions of the user.

[0028] According to a further aspect of the invention, in the method for providing guidance the database further includes at least one connection of one or more targets to at least one question/phrase, where each target represents a link to related information defined by at least one user and strength is assigned to each connection by aggregating information from the collection of paths of all users or from segments thereof, that are associated with the same objective, and according to the popularity of usage of said connection among all users.

[0029] According to a further aspect of the invention, in the method for providing guidance the database further includes at least one promoted connection having biased strengths to questions/phrases and/or targets of the initial model.

[0030] According to an aspect of the invention a system for assisted information collection, is disclosed, the system including: a tangible memory module, operable to store a connectivity model which includes a database of inquisitive statements and of connection strength evaluations of connections between the inquisitive statements; wherein the database includes at least a first inquisitive statement, a plurality of second inquisitive statements connected to the first inquisitive statement, and connection strength evaluations of the plurality of connection between the first inquisitive statement and each of the second inquisitive statements; an interface for obtaining a selection, of each user out of a plurality of users which selected the first inquisitive statement, of one of the second inquisitive statements as a following inquisitive statement to the first inquisitive statement, out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; and a processor, configured to: (I) determine for each connection out of the plurality of connections a connection strength evaluation based on the selections of the plurality of users, (II) to write the determined connection strength evaluations to the connectivity model; (III) to select, in response to selection of the first inquisitive statement by a new user, a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and (IV) to present the selected set of inquisitive statements to the new user.

[0031] According to an aspect of the invention, a non-transitory computer-readable medium for assisted information collection is disclosed, the non-transitory computer-readable medium including instructions stored thereon, that when executed on a processor, perform the steps of: (a) for a first inquisitive statement selected by a plurality of users, obtaining a selection of each user out of the plurality of users of a following inquisitive statement out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; wherein the set of optional inquisitive statements is selected for the user out of a plurality of second inquisitive statements associated with the first inquisitive statement by a connectivity model stored in a tangible memory module; (b) processing the selections of the plurality of users, to determine a connection strength evaluation for each connection out of a plurality of connections between the first inquisitive statement and a respective second inquisitive statement out of the plurality of second inquisitive statements; (c) writing the determined connection strength evaluations to the connectivity model; (d) in response to selection of the first inquisitive statement by a new user, selecting a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and (e) presenting the selected set of inquisitive statements to the new user.

Brief Description of the Drawings

[0032] Fig. 1A schematically shows an example of the use of the system of the invention according to an embodiment of the present invention;

[0033] Fig. IB shows a feature of storing elected questions on a personal tree, in accordance with examples of the presently disclosed subject matter;

[0034] Fig. 1C illustrates the result of activating a question, in accordance with examples of the presently disclosed subject matter;

[0035] Fig. ID illustrates alternative targets for an activated question, in accordance with examples of the presently disclosed subject matter;

[0036] Fig. 2 schematically shows the graph structure and the tree structure of models of the present invention, in accordance with examples of the presently disclosed subject matter;

[0037] Fig. 3 schematically shows the strength feature of the connections in the system of the present invention according to an embodiment of the invention;

[0038] Fig. 4 schematically shows the inference from the connectivity model to the display screen to the users, in accordance with examples of the presently disclosed subject matter;

[0039] Fig. 5 schematically shows two different trees of different users which are integrated to one mutual tree according to an embodiment of the invention;

[0040] Fig. 6 is an example of the result given to the user by the prior art;

[0041] Fig. 7A schematically shows the method of the present invention; [0042] Fig. 7B schematically shows the method of the present invention for promoted connections.

[0043] Fig. 8 is a flow chart illustrating a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter;

[0044] Fig. 9A and 9B are graphical representations of connectivity models, in accordance with examples of the presently disclosed subject matter;

[0045] Fig. 10 is a flow chart illustrating a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter;

[0046] Fig. 11 is a diagram illustrating a computerized environment in accordance with examples of the presently disclosed subject matter;

[0047] Fig. 12 is a flow chart illustrating additional optional stages of the method of Fig. 8, in accordance with examples of the presently disclosed subject matter.

[0048] Fig. 13 is a flow chart illustrating a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter;

[0049] Fig. 14, 15 and 16 are flow charts illustrating additional optional stages of the method of Fig. 8, in accordance with examples of the presently disclosed subject matter.

[0050] Fig. 17 is a flow chart illustrating a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter; and

[0051] Fig. 18 is a block diagram illustrating system 1800 for assisted information collection, in accordance with examples of the presently disclosed subject matter. It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements. Detailed Description of Embodiments of the Invention

[0052] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention. [0053] In the drawings and descriptions set forth, identical reference numerals indicate those components that are common to different embodiments or configurations.

[0054] Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "processing", "calculating", "computing", "determining", "generating", "setting", "configuring", "selecting", "defining", or the like, include action and/or processes of a computer that manipulate and/or transform data into other data, said data represented as physical quantities, e.g. such as electronic quantities, and/or said data representing the physical objects. The terms "computer", "processor", and "controller" should be expansively construed to cover any kind of electronic device with data processing capabilities, including, by way of non-limiting example, a personal computer, a server, a computing system, a communication device, a processor (e.g. digital signal processor (DSP), a microcontroller, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc.), any other electronic computing device, and or any combination thereof.

[0055] The operations in accordance with the teachings herein may be performed by a computer specially constructed for the desired purposes or by a general purpose computer specially configured for the desired purpose by a computer program stored in a computer readable storage medium.

[0056] As used herein, the phrase "for example," "such as", "for instance" and variants thereof describe non-limiting embodiments of the presently disclosed subject matter. Reference in the specification to "one case", "some cases", "other cases" or variants thereof means that a particular feature, structure or characteristic described in connection with the embodiment(s) is included in at least one embodiment of the presently disclosed subject matter. Thus the appearance of the phrase "one case", "some cases", "other cases" or variants thereof does not necessarily refer to the same embodiment(s).

[0057] It is appreciated that certain features of the presently disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the presently disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.

[0058] In embodiments of the presently disclosed subject matter one or more stages illustrated in the figures may be executed in a different order and/or one or more groups of stages may be executed simultaneously and vice versa. The figures illustrate a general schematic of the system architecture in accordance with an embodiment of the presently disclosed subject matter. Each module in the figures can be made up of any combination of software, hardware and/or firmware that performs the functions as defined and explained herein. The modules in the figures may be centralized in one location or dispersed over more than one location.

[0059] Any reference in the specification to a method should be applied mutatis mutandis to a system capable of executing the method and should be applied mutatis mutandis to a non-transitory computer readable medium that stores instructions that once executed by a computer result in the execution of the method.

[0060] Any reference in the specification to a system should be applied mutatis mutandis to a method that may be executed by the system and should be applied mutatis mutandis to a non- transitory computer readable medium that stores instructions that may be executed by the system.

[0061] Any reference in the specification to a non-transitory computer readable medium should be applied mutatis mutandis to a system capable of executing the instructions stored in the non- transitory computer readable medium and should be applied mutatis mutandis to method that may be executed by a computer that reads the instructions stored in the non-transitory computer readable medium.

[0062] Systems, methods and computer program products are disclosed below, which may be used, for example, for effectively obtainingrequired information from relevant sources, to fulfill one or more objectives that are expressed by a user, and/or for effectively obtaining information from relevant resources by referring to prior indications made by other people about what information is relevant to various situations and how to obtain this information in an effective and meaningful way. Such systems, methods and computer program products may be used to aggregate experience and knowledge from multiple users to provide guidance (questions, words, phrases and data resources) for obtaining this information. Such systems, methods and computer program products may also be capable of (and/or used for) organizing the information effectively and intuitively with connection to the desirable objective.

[0063] By doing so, the entire scope of a situation becomes more clear and understandable to the user. The disclosed methods, systems and computer program products allow the user to understand his knowledge limitations and gaps with respect to the situation he faces and his desired objectives.

[0064] According to an aspect of the invention, there is disclosed a system that uses associations between questions or phrases of one or more words and connections of these questions or phrases to relevant content and/or targets, which may be provided from websites or from users of the data network. Such targets may be any kind of information or content, the identity of individual people, identity of organizations, or tools and applications. For example, targets may include links to Linkedln profiles of people (e.g. expert) or to any other representations of identities on the web.

[0065] Users of the system can create direct connections between questions or phrases and objectives of interest, as well as indirect connections between questions or phrases and objectives of interest, via connections between questions or phrases and other questions or phrases, which are connected to these objectives. These connections may be uni-dimensional or multidimensional and are represented by a connectivity model with varying connection strengths, which is initially based on users' created connections. Then, the strength levels of connections are affected by actions made by all connected users, such that connections between questions or phrases and objectives of interest become stronger if they are used or positively marked by many users. In turn, connections between questions or phrases and objectives of interest become weaker if they are used by few users or negatively marked. This way, progressive accumulation of the wisdom of crowd and collective mind may be utilized by disclosed systems and methods to provide effective guidance to users who wish to obtain required information.

[0066] In an example use scenario, the user first inserts a desirable objective about which he is interested to obtain questions and/or information. If there are questions registered in the system which are connected to the objective of the user, then the system provides the user with these relevant questions. The order of the question presentation is determined among other things by the number of users that used the questions, i.e., the more users used a specific question with connection to a specific objective, the higher priority said question receives in the presentation of the questions. The question that was mostly used by other users is presented first and the question that was least used (if used at all) is presented last, or not presented at all.

[0067] In another example, the user can insert a new objective and new questions to the system. For example: (a) in case when the user inserted a new objective that has not existed in the system before and there are no relevant questions connected to this objective; or (b) in case the user thinks that the questions that existed in the system are not relevant enough or if the user wishes to add some questions of his own, the user inserts new questions and objectives as a part of using the system.

[0068] Normally, most of the users use the questions that already exist in the system and just a number of the users insert new questions. However, this doesn't matter to the fact that the system is inherently built to be updated and evaluated by the users, their level of use of the questions and objectives and the new questions, objectives and targets which they insert to the system. [0069] As discussed below in greater detail, a personal documentation tree (i.e., a personal data structure) may be formed for each user of the system, logging all the activities and operations of that user. Analysis and processing of the information from all trees of a plurality of users may than be used for applying the results to a connectivity model, which provides to the users relevant questions, objectives and targets, based on the connections that were analyzed from the plurality of personal trees of the different users.

[0070] For example, if a user inserts a new question, the question is first added to the personal tree of the user and then it is analyzed and will be applied to the calculated appropriate position in a connectivity model, which determines the order of the presentation of the questions to all users, along with a weight that is assigned to each question. Typically, the more users use the system and insert information, the better is the information that the users can receive from the system.

[0071] Fig. 7 A illustrates global connectivity model 700, in accordance with examples of the presently disclosed subject matter. The global connectivity model 700 is a multi-dimensional graph, which shows the connections between a desired objective of the user and questions and continuation questions, which are relevant to the context of the objective according to other users of the system (e.g., a collective mind). The nodes in the connectivity model 700 are objectives (denoted "O" in Figs. 7A and 7B) and questions (denoted "Q" in Figs. 7A and 7B). The global connectivity model may be implemented such that, in terms of the connectivity model, there is no difference between an objective and a question as they are equivalent, since they both are nodes of the graph and "behave" the same. The difference between the objectives and questions is in the way users understand and utilize the two words.

[0072] The connectivity model 700 shows objective 701, which is connected to questions 711, 712, 713 and 714. Question 712 is connected to continuation questions 715 and 716, and question 713 is connected to a continuation objective 702 and to a continuation question 717. The connection between the objectives and questions in the graph indicates an association of one node to another node in a certain context, where for each connection there is a vector of strengths, which indicates the strengths of the associations between the nodes. The vector of strengths indicates the strength of connections in different terms/contexts between the nodes such as, the strength in term of geographical locations, the strength in term of timing, the strength in term of medical condition and so on. For example: objective 701 is connected to question 714 with a strength vector 724. The vector 724 may show strong connection between the objective 701 and the question 714 in a geographical location A, weak connection strength in a geographical location B and medium connection strength in a geographical location C. The multitude of strengths creates another dimension of the graph.

[0073] Connectivity model 700 also has another dimension of targets (denoted "T" in the examples of Figs. 7A and 7B), which are information sources (such as other websites, a search engine that can provide answer to that question, identity information of an individual or an organization, a tool or an application, or any external resource) and/or links to such information sources, to which the user can apply and activate the question.

[0074] Each node may be connected to one or more targets, where each such connection has a multitude of strengths, one for each context. As can be seen in Fig. 7A, question 711 is connected to three targets, 751, 752 and 753. The questions and the targets were all inserted to the system by the users of the system.

[0075] The questions in connectivity model 700 are not functioning only as a way of providing information, but may optionally also be used as objects by themselves that can be shared in social media or otherwise used. Hence, a user can define an objective and receive as a result from the system a question, which is relevant to the defined objective, and can be used elsewhere. Generally, the system guides the users what to ask in order to receive the necessary information.

[0076] Embodiments of the present invention will be better understood through an example as presented below:

Example 1 :

[0077] If a user is interested in planning a trip, after he connects to the system by accessing the service, the first screen that is presented to the user asks him to define the objective that the user want to perform or achieve. In this example, the objective is "plan a trip to the U.S.". Fig. 1A schematically shows a first screen that may be presented to the user (denoted 50), in accordance with examples of the presently disclosed subject matter.

[0078] After the user defines the objective, the system presents a second screen 51 (an example of which is schematically shown in Fig. IB which shows a user interface screen, in accordance with examples of the presently disclosed subject matter), where different kinds of questions that are relevant to that objective and that other users defined as issues to be considered while fulfilling the objective are presented.

[0079] The screen in the illustrated example is divided into two parts: the "personal data structure" part 151 and the Graph part 152, which represents a view into the structure of connectivity model. [0080] In the Graph part 152, questions are presented under the objective the user defined in the first screen of Fig. 1 A. In the present example, and as can be seen in Fig. IB, the questions are:

[0081] What is the best time of the year to visit in U.S.A.? (Question 1)

[0082] What to consider before planning a trip heads for U.S? (Question 2)

[0083] What types of hotels are in the U.S.A.?

[0084] What are the best states to travel with children?

[0085] Objective - Cruise planning in the U.S.A.

[0086] Objective - Visiting in New York

[0087] If the user selects the question/objective: "Objective - Cruise planning in the U.S." - the system continues to assist the user in planning a cruise as part of the objective of planning a trip to the U.S.

[0088] The system can also present other objectives that are connected to the desired objective of the user and it is possible to plan and achieve more than one objective and also an objective within an objective.

[0089] Optionally, the name of the user that originally inserted a question into the system is shown next to each question. In addition, the users in the illustrated example can mark the question with an "irrelevant" button 154. There is also the "more" button 155, which enables to see more questions that other users considered would be relevant to ask after the specific question. Technically, the questions under the "more" button 155 are the questions in the connectivity model that are connected to said specific question with respect to the objective that the user inserted. The user can surf over the different questions and objectives "Backward" and "Forward" as he wishes.

[0090] When the user presses the "More" option button 155 on the question "what types of hotels are in the U.S.? the following questions/objectives are presented:

[0091] What is the best hotel chain to order cheap hotels in in the U.S.?

[0092] What are bed and breakfast (B&B) hotels?

[0093] Are there casino hotels in the U.S.?

[0094] Where is the best location for resort hotels?

[0095] Best places to sleep them in the U.S.?

[0096] How to book a room in the U.S?

[0097] If the user is interested in activating a question in the targets, he presses the "Activate"+ "B" buttons 156 and 160, respectively. The user can also share the question in social networks such as Facebook, Twitter etc., by pressing the "Use" button 158. The user can also suggest questions that he thinks are relevant using the button "suggest a question/objective" 157. The user can also search for questions that are not connected to the objective he originally inserted and can also look for other objectives in the global connectivity model. Then, if he thinks that a question or an objective that he found is related to the original objective, he can add them and embed them into a connection to the original objective which he inserted.

[0098] In the Graph part 152, the system also presents information from relevant data sources (such as websites), for example websites for searching answers to the questions that the user selected. The relevant websites are presented after the user presses the B button 160 under the "Targets" category, while the first website on the list is the one that got the highest strength, the second website on the list got the second highest strength, and so forth. The user selects the target where he likes to activate a question and then he is automatically directed to the relevant web page, in case the target is on the web. The user can save the web page (or link to the web page) for future reference, as a choice he made by pressing the ' V ("yes") button, the "?" ("maybe") button or the camera ("capture") button. The web page, including the exact web address is saved in addition to the screenshot of the page. All the information the user wanted to save is connected to the user's personal tree under the relevant question, so that the user can see the question and all the information that he connected to that question on the screen (i.e., the information he saved) according to the decisions he made.

[0099] The suggested selection of targets is based on aggregation of targets used from the personal navigation paths (trees) of all users, and therefore, is also based on the collective mind and wisdom of the crowd.

[00100] Fig. IB also shows another feature of dragging elected questions from the Graph part 152 to the personal data structure 151. After questions 1-4 were presented to the user (on the right part of the screen). In this example, the user dragged Questions 1 which was selected in "maybe" category and Questions 2 which was selected in "Yes" category, to his personal data structure (on the left part of the screen). Both the navigation between questions and the storage of elected questions in the personal data structure affect the strength of the relevant connections in the global connectivity model, while a higher weight is assigned to the stored questions. As a result, the effect of the stored questions 1 and 2 on strengthening of the relevant connections in the global (connectivity model) will be more substantial than the effect of questions 1 and 2, which were navigated but not elected. The same applies to the promoted question 5, which has initial connections with higher (biased) strengths. [00101] Fig. 1C illustrates the result of activating a question (screen 52), in accordance with examples of the presently disclosed subject matter. In this example, the content from the target www.booking.com which is currently connected to that question with the highest strength will be displayed on the right.

[00102] Fig. ID illustrates an option of selecting a different target for the activated question (screen 53), in accordance with examples of the presently disclosed subject matter. In this example, a submenu will be prompted to the user, suggesting 3 alternative targets for answering the activated question (www.expedia.com, www.easyjet.com and www.salsa.com). The order of alternative targets reflects the current strength of connection of each alternative targets to that question. Upon selecting an alternative target, these strengths will be updated accordingly in the global graph.

[00103] In addition, the present invention allows the user to organize the information he chooses to save under titles he creates. Moreover, the user may add notes to the saved information.

[00104] Referring to the examples provided in relation to Figs. 1 A, IB, 1C and ID, it is clear that the user interfaces, the questions themselves, and the interrelations between data structures and entries are merely examples, and that the disclosed invention is not limited to such an implementation.

[00105] An engine which includes two data structures is disclosed, where that engine can manage the questions of the users and the activities of the users. The first data structure is a Global/Universal connectivity model. This data structure (which may be implemented, for example, as a graph) comprises all the questions and activities that are stored in the system, including directed links between the entities (i.e., links between questions and objectives question and questions, objectives and objectives etc.). The directed links between entities in the graph may be represented by multi-dimensional vectors of connection strengths, where the strength in each context (such as geographic location, etc.) is represented by a coordinate of said vector.

[00106] It should be noted that the objectives may also be implemented as a type of questions with a special feature of an objective. In such cases, when a user inserts in a predetermined field (such as suggest a question) a new question/objective which doesn't exists in the data base, the question/objective is automatically added to the global model graph after being analyzed and processed as explained above.

[00107] Once the user selects an objective at the beginning of the process, the system proposes to the user to see questions that are related to the desired objective by selecting questions which are linked in the global connectivity model to the desired objective. Optionally, every question can be linked in the global connectivity model to every other question and to other objectives. Also, every objective can be linked to other questions and to other objectives. Eventually, all the links between all the entities create the directed graph, where each entity can be connected to any other entity (possibly subject to connectivity rules or scheme, which may limit connectivity between some types of objects).

[00108] The order of the questions and the transition of the user between them are also important, since the transition between two questions can lead to creation of a new connection in the graph, even if the question already exists in the system. Therefore, the created graph is a directed graph, which describes the direction of the questions, i.e., which question will come before and which after. The directed graph reflects, for each question, what most of the users have chosen to ask after they have asked that specific question. It is noted that two questions may optionally be two- way linked, in two one-way connections. That is, the node of a first question may point to the node of the second question as a continuation question which some user asked, while the node of the second question may link to the node of the first question as a continuation question asked by other users for this questions. For example, user which were interested in "how much does it cost to rent a car in Venice" may be interested in "how much does it cost to rent a gondola in Venice", and vice versa.

[00109] A node in the graph can also be connected to some potential targets. The questions and objectives are independent entities and the system may be configured to register for each entity where users think said entity should be activated to get an answer. Hence, the question is activated according to the selected target, which can be a dedicated search engine, a specific web page with an answer that someone provided, specific data source or even a generic search engine such as Google. Targets are ordered and provided to users according to previous selections of the plurality of users of the system (i.e., the "crowd").

[00110] It is noted that optionally, some questions, objectives and/or targets may be also provided by other entities, such as by paying commercial providers. For example, a hotel ranking website may wish to be listed as a target for some questions (e.g. "which is the best hotel in Lima, Peru?") and to pay for such opportunity. Optionally, the amount which the commercial provider may be requested to pay may depend on the value assigned to his targets by users of the system (either explicitly or implicitly by their activities and choices). For example, the cost of promotion may be a function of the relevancy of the spot to that commercial entity. The more relevant it is - the higher the price. Prices are determined by the market.

[00111] As mentioned before, the questions are independent entities and therefore, they may connected to more than a single objective, based on where users choose to use said question and to what question or objective to connect it. For example, the question "how to explain things to children" may be related to the objective of relocating to another country, but also to the objective of dealing with a serious medical condition. Basically, the system suggests usage options for the question, such as sending by email the question, or sharing in a social network, or exporting the question to a "questions - answers" websites, etc.

[00112] The system connects to the global graph actions/operations that users perform with a specific question, together with strength parameter which is influenced by the number of users that have done the same action with the same question. It is possible that the question will not have a target connected to it, where the graph only provides the actions that other users have done with this question.

[00113] Every combination of question and objective can be associated with features that contain characteristics of the combination, for example: the profile of the composer of the question, the time of creation of the question, etc.

[00114] The second type of data structure is the personal data structures which are built for each user and which track and store the user's navigation and actions on the previously described graph. The personal collection of data structures contains questions and objectives that were selected by a specific user during the interaction with the system. Each such personal data structure stores elected questions/phrases with their associated objectives (e.g. which are dragged by the user from his navigation paths among the questions/phrases and objectives), while the desired objective is the root of the personal data structure.

[00115] One user can have more than one personal data structure, depending on the usage of that user in the system. Also, each user can have more than a single type of personal data structure for the same objective. For example: one data structure can store the user's navigation path among different questions, and another data structure can describe elected questions, decisions of the user and files related to it.

[00116] When a user selects a question or an objective from the graph, a new node for that question or objective is created in his personal navigation path, and all the information and operations the user performs with respect to the specific question (for example, activating a question, capturing some data received in response to a question etc.) is stored in that personal navigation path so that the system can later on aggregate this information from many users and update connection strengths in the global graph.

[00117] Fig. 2 schematically shows the two models of an engine, in accordance with examples of the presently disclosed subject matter. The models include a first model (also referred to as "graphic static model", denoted model 61) and a second model (also referred to as "instances model" or "tree instances model", denoted model 62). The user can perform various actions with information provided to him by the system. For example, the decisions that the user can perform with respect to the information that is provided to him by the system can be divided into three categories/types of connection:

[00118] The first decision is "capture", which is a general category where the user is interested to save the information for a future use, or any other reason.

[00119] The second decision is "yes" - this decision usually means that the user is interested in the information as a good answer for the question he asked.

[00120] The third decision is "maybe", indicating that the user is not sure about the relevancy of the information provide to him, but he would like to keep it as an option. The "maybe" decision and the "yes" decision can be replaced with each other and a "capture" decision can be made for both of them. The user can also add a title, features and notes to each of the decisions.

[00121] Optionally, each connection between questions, objectives and targets is featured with a strength parameter, which is influenced by the level of correlation between personal navigation paths (either in their entirety or partial segments of them). Generally, the more users implicitly indicated about such a relation, the stronger the connection is, and the higher priority those connected entities receive when presenting questions/activities to the users. The strength parameter is a dynamic parameter, as it changes from time to time according to the selections of the users, and it is determined by a large variety of usage parameters.

[00122] Optionally, the system may enable a promoted connection between entities (questions/objectives/targets) where in this case, two types of connections are created between said entities. The first one is the standard connection, which is created as described above by users, either explicitly or based on actions and selections of the users. The second type of connection is marked as a promoted connection.

[00123] Entities which are related to questions/objectives by a promoted connection may be displayed to users in a designated area of their screen. It is noted that this is not necessarily so, and that promoted entities may also be displayed together with non-promoted entries, and may be either indicated as promoted or not so. The promoted connection is usually created to promote a specific entity, (for example a new website that should be exposed to the crowd, or a new question which is not popular enough to appear in the list of questions that is derived from the global connectivity model by connection strengths). In this case, the strength vector of the standard connection is affected by the usage of the promoted connection, so that the more users use the promoted connection, the standard connection becomes stronger. This is also a way to introduce new questions/objectives/targets and give users the opportunity to affect and improve the strength of connections between questions and targets in the global connectivity model simply by using said introduced entity and preferring it over existing ones.

[00124] Fig. 7B schematically shows the connectivity model in the case of promoted connection, in accordance with examples of the presently disclosed subject matter. The connectivity model of Fig. 7B is basically the same as global connectivity model 700 exemplified in Fig. 7A, with one difference: at least some of the connections are determined by promotion, to make the connection promoted (and possibly also based on the number of users that made the connection).

[00125] Fig. 3 schematically shows the strength feature of the connections in the system, in accordance with examples of the presently disclosed subject matter. Fig. 3 illustrates the inference of the strength between entities in the global connectivity model using calculation models that are performed on the data which is collected and aggregated in the personal data structures. A similar technique is used to add new entities or to create new connections in the global connectivity model using a calculation model which is based on aggregation of data from the personal data structures.

[00126] Fig. 4 schematically shows the derivation of questions/objectives/targets from the connectivity model 61 to the display screen 70 of the users, in accordance with examples of the presently disclosed subject matter. For example, the strength of the connection in the global connectivity model may determine the order of the presentation of the questions to the user, or whether the question should be shown at all (e.g. , in case the strength is lower than a predetermined threshold, the question will not be presented).

[00127] Fig. 5 schematically shows two different data structures (trees) of different users which are integrated to one mutual tree, in accordance with examples of the presently disclosed subject matter. The tree 501 of user M and the tree 502 of user Z are personal trees. Each one of them contains the activity X, 503 and question 1, 504. In addition, tree 501 comprises individual entities 505 and 506, which are questions 2 and 8 respectively and also comprises the decisions 509a, 509b and 509c of the user with respect to each entity (capture/yes/maybe), which are not included in tree 502. Tree 502 comprises entities 507 and 508, questions 5 and 9 and also comprises the decisions 516a, 516b and 516c of the user with respect to each entity (capture/yes/maybe), which are not comprised in tree 501.

[00128] Since the two trees have common objectives and questions, a mutual tree can be created (in this case, tree 510 is created). As can be seen, tree 510 is a mutual tree of users M+Z, the tree 510 comprises the mutual entities 503 and 504, but also the individual entities 505 and 506, of tree 501, and the individual entity 507 and 508 of tree 502. It also can be seen that a mutual entity 511 was added to the mutual tree 510, which is mutual to both users but not included in the personal tree of neither one of the users. This mean that entity 511 was added as a mutual entity, either by acceptance of the users in the mutual tree to select this entity or by giving permission to one of the users to select an mutual entity for the mutual tree. The mutual trees are considered as any other tree and therefore effects the model/s which determined the global graph.

[00129] It can also be seen that the decisions of each user 509 with respect to each entity is also saved.

[00130] In another embodiment of the invention, the personal data structures that are created for each user separately can be integrated to a mutual structure which is shared by more than one user, while saving the personal features of each user. This enables collaboration between users who work together to achieve a common objective. The data structure is marked as a mutual one and if all the users of the mutual tree accept a specific action or create the same action (such as activate the same question), the action is marked as a mutual action. Another scenario is possible if one of the members of the mutual data structure receives permission from the rest of the members of the mutual data structure to perform mutual actions. In this case, the action is marked as mutual. The mutual data structure is identical to the personal ones in its behavior and can be viewed and used by each member of the mutual user group.

[00131] The following example clarifies differences between the present invention and existing prior art search engines.

Example 2:

[00132] A user wants to buy a washer. If he uses a prior art engine and types "I want to buy a washer" in the search field, he receives suggestions for queries insert by the user, which are based on the keywords that the search engine identifies in the input field.

[00133] Fig. 6 A schematically shows an example of the question typed in a prior art search engine (Google™) and suggestions received from the prior art search engine (screen 81). Fig. 6B shows the search results that are received from the prior art search engine (Screen 82).

[00134] It can be seen that the main keywords that are identified are "washer" and "buy", and therefore all the results are directed specifically to these keywords. In contrast, the present invention enables the user to select an objective that exists in the system (or to create a new one) and then, after selecting the objective, instead of providing direct answers to a specific question based on keywords, the user is exposed to other questions which are related to the desired objective and that other users recommended asking them with respect to said objective, and to other continuation questions, which are recommended to be asked following a specific question, thus offering the user new aspects and new perspectives of the originally inserted objective. For example, the following questions may be presented to the user: "what parameters should I look into when choosing a dish washer?", "Is there a tradeoff between water and electricity consumption?", "What infrastructure is required to install a dish washer at home?" and "Why placing a dish washer on the right or on the left of the kitchen sink so important".

[00135] Also the user can browse the proposed ensemble of questions and the continuation questions even before turning to seek answers to those questions. If the user so wishes, he can activate the questions in a specific target (e.g. one of the targets that were added to the system by other users) and in this way, receive guidance as to where is it best to find answers to the said question. As an example, the user may receive targets that can direct the user to specialized search engine that would provide the user with answers to the question, or maybe even a direct link to a website that contains the answer to the question. The user can also choose to use the proposed question differently, such as sharing it in social media or sending it by email.

[00136] In addition, in order to document all the services, websites, the user used as well as personal notes, and any other data that the user found relevant, and in order to be able to quickly reach at a later time the information he wanted, the system may optionally allow the user to document some or all of this activities in the system, and/or the information he is exposed to, and he does not need to use external services (as required when using prior art search engines).

[00137] Fig. 8 is a flow chart illustrating method 800 which is a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter. The description of method 800 will be exemplified in relation to Fig. 9A and 9B, which are graphical representations of connectivity model 900, in accordance with examples of the presently disclosed subject matter. It is nevertheless noted that method 900 may use other connectivity models which include the connections discussed with respect to the connectivity model of method 800 (e.g. connections between inquisitive statements).

[00138] Referring to the examples set forth with respect to other drawings of the present disclosure, method 800 may be executed by system 1800, and/or by server 1110.

[00139] Connectivity model 900 is stored as a database in a tangible memory unit. Since connectivity model 900 is intended for prolonged use, it may be stored in a non-volatile memory. Nevertheless, parts of connectivity model 900 may be stored in a volatile memory, at least temporarily, for different reasons (e.g. caching, collecting information before updating the model, and so on). Different data structures may be used to implement connectivity model 900 (e.g. connected graph, etc.).

[00140] Connectivity model 900 includes a plurality of entries 910, each being associated with an inquisitive statement (IS). Generally, each of the first inquisitive statements associated with the different entries 910 is a natural language textual statement, such as a sentence, few sentences, a paragraph, etc. it is nevertheless noted that in some implementations, entries associated with nontextual statements may also be added to the model (e.g. images, videos, sounds, etc.). While not necessarily so, the inquisitive statements of the connectivity model may be natural language proper sentences (including at least a subject and a predicate) which includes a minimal number of words (e.g. minimum three words, minimum 4 words, etc.).

[00141] Some or all of the inquisitive statements may form different kind of sentences (or collection of sentences), such as questions (e.g. "how to fix a flat tire?"), declarative sentences (e.g. "the tools required for fixing a flat tire"), exclamatory sentences ("you'll never have a flat tire again!"), etc. The term "inquisitive statement" is to be construed to include in a non-limiting way all of the meanings of the terms "questions", "phrases", "questions/phrases" and "objective" used above.

[00142] Connectivity model 900 further stores information regarding connections between the entries 910 of the model. Such connections (represented in Fig. 9 by arrows) are directional, and stores information pertaining to transitions from one entry 910 to another. As illustrated, each entry 910 may be directionally connected to more than one other entry 910, but may also may be only pointed by connections from other entries 910 and not pointing to others (e.g. entry ISs of Fig. 9). It is noted that two entries 910 may be connected to each other in two directions (e.g. entries ISs and IS₉ of Fig. 9), e.g. if each of the inquisitive statements (each associated with one of these two entries 910) can lead to the other inquisitive statement of that pair, e.g. as a continuation question.

[00143] Entry ISi pertains to an objective (e.g. "I want to travel to New York this summer", "My printer isn't working", "How to improve yield in production floor level", "improving engine output in my car", "improving bandwidth in wireless connection", and so on.). It is noted that on objective may be pointed to by another objective, or by an inquisitive statement (e.g. as exemplified in Figs. 7A and 7B).

[00144] Also, an inquisitive statement may be pointed to by two different inquisitive statements (e.g. the inquisitive statement associated with entry IS₉), possibly such which originated from two or more different objectives. [00145] Each entry 910 in connectivity model 900 (such entries are also referred to as "nodes") may be connected to one or more targets 950. The targets are information sources (such as other websites, a search engine that can provide answer or further information with respect to an inquisitive statement, or even an external source) and/or links to such information sources, to which the user can apply and activate the question.

[00146] The inquisitive statements and/or the targets may be inserted to connectivity model 900 by users of an implementing system, but such information may also be provided by other sources. For example, targets and inquisitive statements may also be provided by promoting entities paying for their inclusion in the model, by operators of the system, or by a processor which collects other data (e.g. by using cookie data to determine which websites were visited by users after querying the system).

[00147] It is noted that some of the content of connectivity model 900 (e.g. inquisitive statements, connections between inquisitive statements and targets) may be provided by "regular users" of the system (i.e. users to which assisted search is provided by way of suggesting several inquisitive statements to choose from). Users may provide such data explicitly (e.g. by suggesting a target) or implicitly (e.g. by copying an inquisitive statement to a website, which may than be considered as a target).

[00148] However, some of this materials may also be entered by "expert users", which are focused on contributing knowledge to the system (or model), rather than being benefited by the knowledge of others. Such expert users may be actual experts in a field (e.g. a medical doctor or a licensed technician of a given system), but may also be other types of users such as enthusiasts, etc.

[00149] It is noted that a single inquisitive statement may be connected to very different targets or other inquisitive statements, but expert coming from different fields. For example, very different follow-ups to the questions "what to do after a traffic accident" may be provided by a medical expert, by a lawyer, by a policeman, and by a psychologist.

[00150] Reverting to Fig. 8 and to method 800, method 800 includes executing on a processor at least stages820, 830, 840 and 850. and optionally also stage 810.

[00151] Stage 810 of method 800 is performed with respect to a first inquisitive statement selected by a plurality of users, and it includes obtaining a selection of each user out of the plurality of users of a following inquisitive statement out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement. The first inquisitive statement may be an objective, but this is not necessarily so. It may not even be the first inquisitive statement selected by some or all of the plurality of users, but may be just an inquisitive statement selected by all of them, in different stages of their inquiry or discovery processes. Referring to the examples set forth with respect to other drawings of the present disclosure, stage 810 may be executed by processor 1820 and/or by interface 1810.

[00152] As aforementioned, both the first inquisitive statement and the plurality of second inquisitive statements referred to in method 800 may be natural language textual statements.

[00153] The set of optional inquisitive statements is selected for each such user out of a plurality of second inquisitive statements associated by a connectivity model stored in a tangible memory module with the first inquisitive statement. For example, referring to the example of Fig. 9A, if the first inquisitive statement is associated with entry ISs, than the plurality of second inquisitive statements may include the inquisitive statements associated by connectivity model with entries IS2, IS3, IS4, IS5, and ISs (or a subgroup of this group).

[00154] Different sets of optional inquisitive statements may be selected to different users out of the plurality of users. For example, one user may receive a set including inquisitive statements IS2 and IS3, some other users may receive a set including inquisitive statements IS2, IS3 and ISs, yet another user may receive a set of optional inquisitive statements including all of the plurality of second inquisitive statements associated by the connectivity with the first inquisitive statement (entries IS2, IS3, IS4, IS5, and ISs in the illustrated example). It is noted that in many scenarios, there may be much more than five second inquisitive statements associated with the first inquisitive statement by the connectivity model (e.g. about 10, about 100, about 1,000, about 10,000, and so on). Therefore, selecting smaller sets of optional continuation inquisitive statements for the users is important. Optionally, all of the users may receive the same set of optional inquisitive statements (e.g. those with the highest strengths, as discussed above). For the purposes of the present discussion, in order to simplify the description, an inquisitive statement may be referred to by the same label as the entry 910 with which this inquisitive statement is associated in the connectivity model.

[00155] It is noted that the term "second inquisitive statement" does not mean to imply order or hierarchy or different type than the first inquisitive statement, but is used only in order to differentiate this inquisitive statements form the inquisitive statement identified as the "first inquisitive statement" within the context of method 800. It is noted that a second inquisitive statement with respect to one instance of method 800 may be used as a first inquisitive statement with respect to another instance of method 800.

[00156] Stage 820 of method 800 includes processing the selections of the plurality of users, to determine a connection strength evaluation (CSE) for each connection out of a plurality of connections between the first inquisitive statement and a respective second inquisitive statement out of the plurality of second inquisitive statements. Referring to the examples set forth with respect to other drawings of the present disclosure, stage 820 may be executed by processor 1820.

[00157] Several possibly ways of determining CSEs are discussed above (within the context of strength levels, which are examples of CSEs). For example, CSEs of different connections may be affected by actions made some or all of the users connected to the system which interacted with the first question. For example, connections between inquisitive statements become stronger (e.g. receive higher CSEs numerical values) if they are used (e.g. selected) by many users. In turn, connections between inquisitive statements may become weaker if they are used by few users. This way, method 800 may be used for progressive accumulation of the crowd wisdom and collective mind, to provide effective guidance to users who wish to obtain required information based on the knowledge accumulated from many other users. As discussed below in greater detail, connection strength evaluation may be determined by many other parameters, other than (or in addition to) the popularity of selection of each second inquisitive statement.

[00158] In Figs. 9A and 9B, CSEs are denoted 920, and are illustrated in connection to the arrows connecting two entries 910. It is noted that the CSEs may be stored in the connectivity model 900 in different ways (e.g. as standalone entities, as nodes pointed to by an originating entry 910, and so on).

[00159] Stage 830 of method 800 includes writing the determined CSEs to the connectivity model. Referring to the examples set forth with respect to other drawings of the present disclosure, stage 830 may be executed by processor 1820. This may be implemented by updating (or creating) connection strength entries 920 in connectivity model 900 (i.e. in the database stored in the tangible memory unit). The writing includes changing the physical state of memory bits in the memory units (e.g. by changing a magnetic state of memory bits, by changing electric state of memory bits, and so on).

[00160] Stage 840 of method 800 is executed after collecting and processing the selections of a plurality of users (could be any number of past selections, from few selections by few users, to millions of selections and much more), when a new user selects the first inquisitive statement. For example, it may be executed whenever a user selects an existing objective in the system, or when that user chooses a question (or other type of inquisitive statement) which was used by other users before him. It is noted that the new user is not part of the plurality of users whose selections were obtained and processed in stages 810, 820 and 830. Nevertheless, the same process may be executed for a user who is one of the plurality of users (e.g. if revisiting the system, whether for the same objective or for another objective).

[00161] Referring to the examples set forth with respect to other drawings of the present disclosure, stage 840 may be executed by processor 1820.

[00162] Stage 840 is executed in response to selection of the first inquisitive statement by the new user, and includes selecting a selected set of inquisitive statements based on a plurality of CSEs out of the determined CSEs. That is, after the user selected the first inquisitive statement, several follow-up questions (or other types of inquisitive statements) should be presented to that user, e.g. in order to assist him in investigating a subject, fulfilling an objecting, getting more views on a subject, and so on. The selected set of inquisitive statements includes such questions (or other types of inquisitive statements), and is selected based on the CSEs between the first inquisitive statements and a larger number of second inquisitive statements (i.e. larger than the number of questions ultimately selected in stage 840 as the selected set of inquisitive statements). For example, different users (or other entities) may have entered and/or followed hundreds of questions after contemplating the first inquisitive statement, and out of those hundreds of possible questions, only three or four will be presented to the new user (the number of inquisitive statements in the selected set is not necessarily determined in advanced).

[00163] As discussed below in greater details, and also above with respect to various examples, the selection of the selected set of inquisitive statements which will be presented to the user may depend on other parameters, in addition to the history of inquisitive statements selection by other users. For example, some other parameters which may be taken into consideration when computing the selection are user parameters of the new user (e.g. his age, gender, geographic location, previous use history, previous web history, and so on), time parameters, promotions, variety considerations (e.g. giving questions with a low score a chance to be selected by few users, even if scoring low in the past), data from daily news (e.g. if an Tsunami occurred in south east Asia, maybe more people would be interested in dealing with pain and grief, with offering aid, or with commodity prices etc., than in other days of the year).

[00164] It is noted that all of the options and examples discussed above with respect to selection of questions and/or phrases to be presented to users may be implemented as part of stage 840, also with respect to other types of inquisitive statements, mutatis mutandis.

[00165] It is further noted that connectivity model 900 may also include connection strength evaluations between entries 910 and targets 950, where the selection of which targets to provide to the user (similar to the selection of inquisitive statements in stage 840) depends on the CSE between the respective entry (be it the first inquisitive statement or any other inquisitive statement) to the target connected thereto.

[00166] Referring to the selection of stage 840, it is noted that since the inquisitive statement selected for the new user as options are based on the connectivity model - which in turn is based on the way many people investigated a relevant issue (e.g. the objective) - it is possible to provide the new user with angles and ways of thinking which were not at all available to the new user before using the system. For example, if the new user is interested in "how to find an architect?", he may not even be aware of other aspects such as "which architects specialized in green building?" or "how to find whether an architect is registered". Such broadening of the mind is a great opportunity which is not offered in such ways in prior art systems.

[00167] The more perspectives and ways of thinking to which the new user is exposed by the suggested inquisitive statements, the more he is able to find which approach is more fitting to him personally.

[00168] Stage 850 of method 800 includes presenting the selected set of inquisitive statements to the new user. Referring to the examples set forth with respect to other drawings of the present disclosure, stage 850 may be executed by processor 1820.

[00169] It is noted that the presenting of stage 850 may be implemented in different ways, such as displaying on a monitor, displaying on a web user interface, reading as an audio selection (e.g. using text to speech technologies), sending as an HTML data to a computer of the user, and so on. The presenting of stage 850 may also be implemented as providing to another computer the information to be presented to the new user. For example, if the new user is using his home computer, smart phone, or tablet computer to access a web service which offers assisted inquiry process, than a server associated with that web service may send over a web connection (possibly routed between different countries) information of the selected set, which is than received and processed by the computer of the new user, and thereafter presented (e.g. displayed) to the new user.

[00170] Fig. 10 is a flow chart illustrating method 1000 which is a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter. Method 1000 is closely related to method 800 discussed above, but includes user activity in addition to activity of the server. Referring to the examples set forth with respect to other drawings of the present disclosure, method 1000 may be executed by system 1800 and/or by server 1110. [00171] An environment in which method 1000 may be executed is illustrated in Fig. 11, which is a diagram illustrating a computerized environment in accordance with examples of the presently disclosed subject matter. The environment 1100 includes a server 1110, which is configured to execute method 800. Server 1110 may include the tangible memory unit used in method 800, or be connected to an external tangible memory unit (or units). It is noted that the server may include one or more computers, each including one or more processors, each including one or more processing cores. However, in order to simplify the description, all of those one or more processing modules are collectively referred to as the processor of server 1110.

[00172] Server 1110 communicates with a plurality of user computers 1120. Such communication is usually a bidirectional communication, in which server 1110 provides to user computers 1110 sets of optional inquisitive statements (and possibly additional data as well, as exemplified throughout this disclosure), and receives from the user computers 1120 the selections of the users. The user computers 1120 may be connected to the server 1110 directly (either wirelessly - illustrated by dashed lines - or in a wired manner), or through one or more intermediary communication units 1130 (e.g. communication routers, communication switches, and so on).

[00173] As noted above, different kinds of user computers 1120 may be used by different users, e.g. home computers, laptop computers, smartphones, tablet computers and so on. The communication between the different user computers 1120 usually spans over long periods of time (weeks, months, and possibly years), where each user computer 1120 communicates with the server only for relatively short periods during this longer durations (e.g. for minutes or hours at a time).

[00174] Reverting to Fig. 10, during the communication with a system which is operated and managed by server 1110 (such as the systems and computer program product described in the present disclosure, also referred to in a non-limiting way as " research support system"), each user can set (or select) an objective (stage 1010). Some of the objectives selected by different users may be the same (e.g. user 2 and user 3 in the illustrated example), but this is not necessarily so. Pertaining to user i, user i may select the first inquisitive statement (ISi) in stage 1008 either as an objective, or as another type of inquisitive statement. Also - more than one objective may be selected by each of the users during his use of the research support system. Some users (possibly all of the users) may also start using the system without defining an explicit objective for the research support system, as exemplified by user N.

[00175] In stage 1020, each of the users may use the research support system in different ways, some of which were described above (e.g. with respect to Figs. 1 through 7B). Such inquiry process may include, for example, selecting questions, phrases or other inquisitive statement out of proposed inquisitive statements, selecting targets, reading articles and using data resources suggested by the system.

[00176] In stage 1030, a selection of optional inquisitive statement is presented to some or all of the different users (usually in different times), from which they selected the first inquisitive statement (which is the first inquisitive statement of method 800, in the present example). The different sets of optional inquisitive statement are selected based on connectivity model 900.

[00177] It is noted that many other users of the system may not have encountered the first inquisitive statement at all, and some users did receive the option of selecting the first inquisitive statement but opted not to. Nevertheless, the plurality of users referred to in stage 810 (and which is represented by users 1 to N in the example of Fig. 10) included only users which selected the first inquisitive statement as part of the inquiry process with the system.

[00178] In stage 1040, each of the users is presented with a corresponding plurality of optional inquisitive statement, and selects one of them. Users which did not select any options may be ignored (or be excluded from the plurality of users processed in methods 800 and/or 1000), or alternatively their choosing not to continue may be factored in the processing of the CSEs in stage 1060. As can be seen some of the users may receive the same set of optional inquisitive statements (e.g. user 3, user i and user N all receive set W of 5 optional inquisitive statement), but this is not necessarily so.

[00179] It is noted that different users may receive different sets of optional inquisitive statements for different reasons. For example, the different sets may be determined based on user contexts, as explained and exemplified elsewhere in the present disclosure. The different sets may also be provided for other reasons, such as: because the connectivity model changed in the meanwhile between the requests of the different users; because the system tries different variations of sets, to see which work better, and so on.

[00180] The selection of each of the users is recorded (or otherwise obtained) in stage 1050, which corresponds to stage 810 of method 800. After obtaining the selections of the plurality of users in stage 1050, CSEs are computed for some or all of the inquisitive statements which were suggested to users in stage 1040 (stage 1060). Stage 1060 may also include writing the computed CSEs to connectivity model 900. Stage 1060 corresponds to stage 820 (possibly also to stage 830) of method 800.

[00181] It is noted that the computation of the CSEs for connectivity model is not necessarily done once. On the contrary, in many implementations the CSEs may be updated from time to time - when more data is collected from more users. Such additional data may serve not only to refine the results based on larger sets of users, but also to identify and/or correspond to changing trends. For example, when users want to buy a new car, questions relating to fuel consumption may fall out of favor over time, while questions relating to radiations from batteries of electric cars may be more relevant to many more users.

[00182] When the new user uses the system, he may reach his selection of the first inquisitive statement in any of the different ways discussed with respect to users 1 through N. In the illustrated example, the new user first sets an objective (stage 1012, similar to stage 1010 of the other relevant users), than browse through various inquisitive statements and possibly additional data (stage 1022, similar to stage 1020 of the other relevant users), and then selects the first inquisitive statement ISi out of a plurality of options presented to his by the research support system (stage 1032, similar to stage 1030 of the other relevant users).

[00183] After the new user selects the first inquisitive statement in stage 1032, the server should provide the user with several options of inquisitive statement, thereby supporting the user in obtaining more relevant information. The selection of the selected set of inquisitive statements in stage 1070 is based at least on some of the strength connection estimations computed in stage 1060. Stage 1070 also includes presenting the selected set of inquisitive statements to the user. Stage 1070 corresponds to stages 840 and 850 of method 800. In this case, the set presented to the new user is not necessarily the same set W which was presented to users 1..N - it may be different, e.g. based on the strength calculation.

[00184] Reverting to method 800, Fig. 12 is a flow chart illustrating additional stages of method 800, in accordance with examples of the presently disclosed subject matter. Following stage 850, method 800 may continue with stage 860 which includes obtaining a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and with stage 870 of providing to the new user information associated by the connectivity model with the selected inquisitive statement.

[00185] Referring to the examples set forth with respect to the previous drawings, stage 860 may be executed by processor 1820 and/or by interface 1810. Referring to the examples set forth with respect to the previous drawings, stage 870 may be executed by processor 1820.

[00186] It is noted that the determining of CSEs may be executed not only to connections between the first inquisitive statement to other inquisitive statement directly connected to it in connectivity model 900, but for many other connections between entries 910 of connectivity model 900. Especially, connections between the second inquisitive statements to other inquisitive statements which may be reached as continuations of the inquiry process which led different users to select the second inquisitive statements.

[00187] Optionally, method 800 may include repeating the stages of obtaining selections (810), processing the selections of the plurality of users to determine CSEs (820) and writing the CSEs to the connectivity model (830) for one or more of the second inquisitive statements, thereby determining CSEs of different levels of connections with respect to the first inquisitive statement.

[00188] In each such repetition, another inquisitive statement (other than the original first inquisitive statement) is used as the first inquisitive statement for the purpose of the way stages 810, 820 and 830 were discussed above. If an inquisitive statement of the connectivity model which was regarded as a second inquisitive statement in one repetition is later used as a first inquisitive statement in another repetition of stages 810, 820 and 830 - a series of connections are analyzed, and different hierarchical levels can be analyzed.

[00189] For example, while inquisitive statement ISs in Fig. 9 A can be analyzed as a direct continuation question for inquisitive statement ISi, it can also be analyzed as a continuation question of inquisitive statement IS₉, which in turn can be a continuation question of inquisitive statement IS4, which yet in turn can itself be a continuation question of first inquisitive statement ISi. Therefore, inquisitive statement ISs may also be analyzed as a third level hierarchy question with respect to the original first question ISi. , and may be more (or less) likely to be selected after inquisitive statement IS9 was selected than it was likely to be selected as a direct follow up of ISi. It is noted that the term "question" was used in this paragraph instead of the more general term inquisitive statement for simplicity of writing only, and that any of inquisitive statement ISi, IS4, ISs and IS₉ may be any kind of inquisitive statement, and not necessarily a question.

[00190] Optionally, method 800 may further include normalizing, with respect to each other, the CSEs of connections stemming from each second inquisitive statement out of the one or more second inquisitive statements. This may be extended to other entries 910 of the connectivity model (possibly for all of them).

[00191] For example, in the example of Fig. 9A, the CSEs of connections stemming from each entry 910 are normalized, so that the sum of all the CSEs of connections stemming from any single entry 910 is equal to one. The CSEs are illustrated as a decimal fraction within ellipses located on the respective connection (represented by an arrow between two entries).

[00192] In the illustrated example, inquisitive statement ISs is relatively much more likely to be selected as continuation of IS9 than it is likely to be selected as continuation of ISi (0.7 as opposed to 0.4). However, it is possibly that since ISi is selected much more often than IS₉, most of the times IS8 is selected would be a continuation of ISi, and not of IS₉. It is noted again that this is just one example, and that other algorithms, decision rules and/or selection criteria may be used.

[00193] It is noted that the CSEs are not necessarily indicative of the number of times each of the second inquisitive statements is selected, but may also take into considerations other factors. An inquisitive statement with a relatively low CSE associated with which may be selected very often - but most users than quickly choose to go back to the first inquisitive statement, in order to select another inquisitive statement (which means the often selected inquisitive statement was not useful for them, and therefore should receive a low CSE).

[00194] Fig. 13 is a flow chart illustrating method 1300, which is a variation of method 800, in accordance with examples of the presently disclosed subject matter. Optionally, method 800 may include repeating stages 810, 820 and 830 for multiple level of connections (a connection leading to entry A and a connection leading from entry A being connections of two different consecutive levels, within the scope of the present disclosure). Method 800 may further include repeating stages 840 and 850 for the new user, i.e. repeating the selecting of a selected set of inquisitive statements for each of a series of selecting by the new user of inquisitive statements out of selected sets of inquisitive statements (i.e. for several times, each time the new user selects one IS of the set presented to him, another set of ISs is selected and presented to the new user, for further selection). In cases the new user selected an objective as the first inquisitive statement, this results in exposing the new user to a group of inquisitive statements which are relevant to an objective of the user as selected by selecting the first inquisitive statement.

[00195] Method 1300 includes two general processes, process 1301 in which the connectivity model is updated based on user activity (selections of many users), and process 1302 in which the connectivity model is used in order to successively provide to a new user (or a plurality of new users) successions of sets to select inquisitive statements from, as described in the previous paragraph.

[00196] Process 1301 includes stages 1310, 1320 and 1330, which are repeated several times, for different inquisitive statements (even though some repetitions for a single inquisitive statement may also be implemented). Stage 1310 includes obtaining, for a given inquisitive statement, selections of a plurality of users of following inquisitive statement out of sets of optional inquisitive statements which are selected based on the connectivity model. Essentially, stage 1310 includes executing stage 810.

[00197] Stage 1320 includes determining CSEs for connections between the given inquisitive statement and various inquisitive statements connected to the given inquisitive statement in the connectivity model, based on the selections of the plurality of users (and essentially includes executing stage 820). Stage 1330 includes writing the determined CSEs to the connectivity model, thereby updating the connectivity model (and essentially, stage 1320 includes executing stage 830). It is noted that while in the illustration, each repetition is executed after another repetition is finished, this is not necessarily so. Also, several instances of stage 1310 may be executed (for one or more given inquisitive statements), and the information of selections collected for all of these instances may be used for a single instance of stage 1320.

[00198] Process 1302 includes stages 1340 and 1350, and may also include optional stages 1360 and 1370. Stage 1340 essentially includes executing stage 840, stage 1350 essentially includes executing stage 850, stage 1360 essentially includes executing stage 860, and stage 1370 essentially includes executing stage 870.

[00199] As mentioned above, e.g. with respect to Fig. 2, 3, 4 and 5, the history of individual users may be recorded in dedicated data structures (each storing information pertaining to a single user, or to a group of several users - e.g. collaborating group of users). Such data structures may be trees (as discussed above with respect to personal trees), but other types of data structures may as readily be used. It is noted that all the information stored in a personal tree as discussed above may be saved in another type of personal database, mutatis mutandis. It is noted that the uses of personal trees as discussed above may be implemented using other types of personal data structures, mutatis mutandis. It is noted that any referral above to a personal tree or other type of personal data base may be implemented as pertaining to an entry (or entries) associated with a single user in a data structure which stores information of many users. For example, linked lists may be used as personal data structures, instead of trees.

[00200] Fig. 14 is a flow chart illustrating additional stages of method 800, in accordance with examples of the presently disclosed subject matter. Optionally, method 800 may include stage 880 of obtaining for each user out of the plurality of users a sequence of selections of inquisitive statements by the user (e.g. a "path" of the user), the sequence defining a path between entries of different inquisitive statements in the connectivity model. This may be implemented, for example, using a personal trees as discussed above, or using other data structures. It is noted that obtaining of a path may be implemented for users of the system which do not belong to the aforementioned plurality of users (e.g. for users who did not select the first inquisitive statement). Referring to the examples set forth with respect to the previous drawings, stage 880 may be executed by processor 1820 and/or by interface 1810. [00201] Stage 880, if implemented, is followed by stage 890 of storing the sequence of selections (for each users of the plurality of users) in a data base stored on a non-volatile memory storage. Referring to the examples set forth with respect to the previous drawings, stage 890 may be executed by tangible memory module 1830.

[00202] The plurality of paths (or sequences) of the different users may be used for different utilizations, e.g. as discussed above with respect to personal trees. For example, stage 890 may be followed by stage 8100 and stage 8110.

[00203] Optional stage 8100 includes analyzing the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements. Referring to the examples set forth with respect to the previous drawings, stage 8100 may be executed by processor 1820.

[00204] Optional stage 8110 is executed in response to selection of the first inquisitive statement (by the new user, or by any other user), and includes presenting the at least three inquisitive statements simultaneously. Referring to the examples set forth with respect to the previous drawings, stage 8110 may be executed by processor 1820.

[00205] Referring to stages 8100 and 8110, after processing information from many users, a pattern may be identified, according to which a great part of these many users select a relatively small set of inquisitive statements, shared to all of these users. It is noted that not all of those users necessarily choose the small set of inquisitive statements in the same order (albeit this may be a requirement, or the order may be considered when identifying the frequently occurring path).

[00206] For example, it may be identified that out of all of the users which selected "dealing with death of a parent" , many users selected throughout their use of the system the following inquisitive statements: "How to organize a funeral", "What happens at a reading of a will", "How to deal with a loss of a loved one as a family" and "How to maximize your profit when selling an apartment", and usually in that order.

[00207] Therefore, when another user chooses "dealing with death of a parent" as an objective, it may be useful to present to him all of these steps he is likely to encounter together (e.g. on a single screen of a web user interface). The user than knows what he is likely to go through, what is a likely order to cope with the different faces of the situation he encountered. The user can also access each of those inquisitive statements (e.g. according to their order, but not necessarily so), and keep returning to the set of inquisitive statements as a hub, or a starting point, to keep exploring from, in various fields. [00208] It is noted that a non-ordered set of frequently occurring inquisitive statements may be used instead of the path, wherein for a large group of users, each of these users have selected all (or most) inquisitive statement of the non-ordered set when using the system. The frequently occurring path (or set) may be related to a specific objective, but this is not necessarily so.

[00209] It is noted that stage 890 may also be followed by a sequence of stages which enable using of frequently occurring paths which include targets (with or without inquisitive statements) selected by many user. In such cases, the targets may be activated automatically for the user, e.g. by a dedicated Application programming interface (API). Such targets may be websites, applications (e.g. on mobile devices or tablet computers), other software, external electronic devices, or remote computers.

[00210] Optionally, stage 890 may be followed by a more general variation of stage 8100, which includes analyzing the paths of the plurality of users to identify at least one frequently occurring path which identifies an ordered set of at least selections common to a plurality of users. The selections may be selections of inquisitive statements (as is the case in stage 8100), but may also be other selections such as selection of targets, selection of activities in other software products (if followed), in other device (if followed), and so on. For example, it is possible to note that many people who asked the question "what to do with a flat tire" turned on a flashlight application on their cellular phone after placing a call to the police.

[00211] This generalized version of stage 8100 may either be followed by stage 8110, or by a more general variation of stage 8110, which includes providing information of items of the frequently occurring path to two or more systems. This item information may be provided simultaneously, but this is not necessarily so. One of the systems may be the system which executes method 800. At least one of the system is a system which is external to the system which executes method 800 (i.e. have no physical connection between the external system and the system which executes method 800, except an optional data communication channel, such as a data cable etc.).

[00212] Referring to the more general variation of stages 8100 and 8110, an example implementation is a common objective of many users "plan a weekend in Rome for first timers". The frequently occurring path selected based on the experience of large number of users may in such case include a travel itinerary (including a plurality of locations to visit, e.g. at a favored order), and possibly additional items, e.g. pertaining to topics such as where to stay, where to it, and what to do with children. The generalized stage 8110 in such an example may include activating other applications (e.g. on a cellular phone or another computer of the new user), such as activating the best value website for ordering a hotel to which information was provided for determining which is the most recommended hotel for the user based on his profile (e.g. business trip, romantic vacation, family vacation, etc.), activating an application for selection of flight seat (e.g. Seatguru), and activating one or more other applications for ordering tickets to recommended sites for first timers and to the most suiting restaurants.

[00213] As mentioned above, information may be provided not only to applications, but also to physical devices. As an example, a passenger of an autonomic vehicle may report a chest pain (either explicitly or implicitly, e.g. by pressing a dedicated button, by asking an intelligent personal assistant, by writing a textual inquisitive statement, etc.). The system which executes method 800 may receive information from other systems (e.g. receiving physiological data from physiological sensors such as blood pressure and pulse sensors). Such additional information may be transferred to other systems, and may also be also used as a context (e.g. different frequently occurring paths may be determined for users whose pulse exceeds 140 BPM and to user with lower pulses).

[00214] The generalized stage 8110 in such an example may include providing information to other systems based on the frequently occurring path determined based on the experience of many other users. For example, it may provide a cellular phone of the user information for calling a nearby hospital or for sending a message indicating that a patient with a probable heart attack is coming; it may provide the autonomic car with navigation directions for the nearby hospital; it may provide the cellular phone instructions to send text messages to relatives. It may trigger a transmission of physiological parameters of the user from the sensors to the hospital, and so on.

[00215] Fig. 15 is a flow chart illustrating additional stages of method 800, in accordance with examples of the presently disclosed subject matter.

[00216] In addition to obtaining the selections of the following inquisitive statements at stage 810, method 800 may further include stage 815 of recording, for at least one second inquisitive statement, activities of different users which are associated with the respective second inquisitive statement. Referring to the examples set forth with respect to the previous drawings, stage 815 may be executed by tangible memory module 1830 and/or by processor 1820.

[00217] For example, the recording of stage 815 may include recording how much time did different users spend in links, targets or other inquisitive statements related to the respective second inquisitive statements, how often did they return to this respective inquisitive statement in order to study other aspects related to it, did they mark it as relevant or irrelevant, did users interact with the respective second inquisitive statement in any of the manners exemplified above (e.g. saving it for future reference, etc.). The recording may include recording of social activities (e.g. sharing an inquisitive statement on social networks, activities such as favorite, hide or share, and so on.

[00218]

[00219] If stage 815 is implemented, the determining of the CSE for the at least one second inquisitive statement in stage 820 is further based on the recorded activities (for one or more of the at least one second inquisitive statements for which activities were recorded, possibly for all of them, denoted stage 825).

[00220] Fig. 16 is a flow chart illustrating additional stages of method 800, in accordance with examples of the presently disclosed subject matter.

[00221] Optionally, stage 810 may further include stage 812 of obtaining selection related parameters associated with each of the selections of the plurality of users. Stage 820 in such case may include stage 822 of processing the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the CSE as a connection strength vector which includes at least two connection strength values. For example, a vector CSE may be implemented as a vector (CSVi, CSV2, CSV3, . . . , CSVN), where each CSV; is a scalar connection strength value. It is noted that a CSE which includes multiple connection strength values (CSVs) is not necessarily implemented as a vector (e.g. it may be stored as a matrix), but for convenience of disclosure, for the purposes of the present disclosure the term "CSE vector" (and related terms, mutatis mutandis) pertain to any CSE which includes multiple CSVs.

[00222] The selecting of stage 840 - in cases where vector CSEs are used (exclusively or in combination with scalar CSEs) - includes stage 842 of selecting of the selected set of inquisitive statements is based on a subset of connection strength values of each of the plurality of CSEs, the subset being selected in response to user parameters of the new user.

[00223] It is noted that an example of a connectivity model 900 in which the computed strength are implemented as vector is provided in Fig. 9B. it is furthermore noted that in a single connectivity model 900, some of the connections may be assigned a scalar strength while others are assigned a vector CSE.

[00224] A vector CSE may be implemented for indication of association of one entry (or node) 910 to another entry 910 in different contexts, where different CSV (or groups of CSVs) pertain to the connection between the respective two entries 910 in a certain context, such as geographical context (e.g. users from different countries may be analyzed separately, because they show different patterns of inquiry, or different interests), temporal context (e.g. users inquiring a subject in different parts of the day - or of the week, month or year - may be analyzed separately, because they show different patterns of inquiry, or different interests), language, use patterns (e.g. user who tends to read each target in length in comparison to other who only pay a cursory review to most targets before they move on to the next inquisitive statement), and so on.

[00225] Other optional factors which may affect the CSEs (or specific CSVs within a CSE) are search history and objective. For example, the question "how can balance be learnt" may have different meaning for users seeking to balance family life and work and for users who started learning how to walk the tight rope.

[00226] With respect to the entire discussion of method 800 above, it is noted that different combinations of stages where discussed with respect to different Figs. It is noted that the discussions of different optional aspects of method 800 where discussed with respect to different drawings were done for reasons of convenience and clarity of disclosure, and are not to limit the invention in any way. It is noted that any combination of stages 812, 815, 822, 825, 842, 860, 870, 880, 890, 8100 and 8100 may be part of method 800 (which includes at least stage 810, 820, 830, 840 and 850) and could be implemented together, even if not explicitly elaborated. This holds for every such combination in which preceding stages are included for any stage of the combination. For example, since stage 822 is required as a preceding stage for stage 842, any combination which includes stage 842 must also include stage 822. Stages 1301, 1302, 1310, 1320, 1330, 1340, 1350, 1360, and 1370 may also be included in any such combinations.

[00227] Reverting to Figs. 9A and 9B and to connectivity model 900. Connectivity model 900 includes a plurality of entries 910, each being connected by connectivity model to other entries 910 (and some also to targets 950). As demonstrated in the discussion above with respect to method 800, and especially to stages 840 and 850, the information in connectivity model 900 relating to which inquisitive statements are connected to which other inquisitive statements, and what are the CSE for such connections - may be used in order to select which inquisitive statements to offer to the user for selection.

[00228] The usefulness of the connectivity model 900 for selecting and suggesting inquisitive statements to the user may be achieved even if connectivity model 900 is built in another way than the one described with respect to stages 810, 820 and 830.

[00229] As mentioned above, personal data structures may log which inquisitive statement did each user watch, selected, followed, or otherwise interacted with. While personal data structures may include information of such user activity which was collected by suggesting to the user sets of inquisitive statements which were selected based on the connectivity model, the personal data structures may also include information collected in other ways.

[00230] Fig. 17 is a flow chart illustrating method 1700 which is a computer-implemented method for assisted information collection, in accordance with examples of the presently disclosed subject matter. Method 1700 includes executing on a processor at least stages 1710, 1720, 1730, 1740, and 1750.

[00231] Stage 1710 includes obtaining, for each user out of a plurality of users, search history which includes information of inquisitive statements used by the user with one or more web search systems over at least one search duration of the user. For example, when using a traditional search engine, the user may enter as search queries (or select from autocomplete suggestions of the search engines or from other suggestions such as promoted connections) several inquisitive statements. Usually, such inquisitive statement will be entered to the search engine in succession and not concurrently, and would therefore have an order, defined by succession of time.

[00232] It is noted that the web search system (or systems) from which search history are collected may include a wide range of web search systems such as: search engines, social networks, internet forums, and so on.

[00233] Since the inquisitive statements of method 1700 may be ones which are freely used by users of the one or more web search systems (as opposed to selected from a limited number of prestructured inquisitive statements), there may be a need to group information from several phrases used by different users to one inquisitive statement. Naturally, this may be repeated for different inquisitive statements, each being associated with different search queries or other forms of inquisitive statements. For example, the same inquisitive statement may appear in different forms of spelling (or misspelling), in different order of words in the sentence or in a different style, while still pertaining to the same idea. For example, all the inquisitive statements "where to buy a pretzel in NY", "where to buy a pretzel in New York", "were to buy a pretzel in NYC" and "NY where to buy pretzels" could all be associated with a single inquisitive statement.

[00234] Therefore, method 1700 may optionally include stage 1715 of 1715 associating to a single inquisitive statement information of a plurality of inquisitive statements used by different users. As aforementioned, stage 1715 may be repeated for different inquisitive statement. It is noted that in some situations, a similar stage may also be used in method 800, between stages 810 and 820 (e.g. referring to questions in different languages, or formatted to different audiences).

[00235] Method 1700 continues with stage 1720 of processing the plurality of search histories of the plurality of users, to determine connection strength evaluations for a plurality of directional connections between inquisitive statements used by the plurality of users. The determining of the CSEs in stage 1720 may be implemented similarly to any option discussed with respect to stage 820 of method 800, mutatis mutandis.

[00236] Stage 1730 of method 1700 includes writing the determined connection strength evaluations to a connectivity model. The writing of stage 1730 may be implemented similarly to any option discussed with respect to stage 830 of method 800, mutatis mutandis.

[00237] Stage 1740 of method 1700 includes selecting a selected set of inquisitive statements out of the inquisitive statement of the connectivity model. The selecting of stage 1740 is based on CSEs of the connectivity model and on a search history of a new user (the search history of the new user including at least one of the inquisitive statements of the connectivity model, or an inquisitive statement which could be connected to the inquisitive statement of the connectivity model in ways discussed in relation to stage 1715). The selecting of stage 1740 may be implemented similarly to any option discussed with respect to stage 840 of method 800, mutatis mutandis.

[00238] Stage 1740 is followed by stage 1750 of presenting the selected set of inquisitive statements to the new user. The presenting of stage 1750 may be implemented similarly to any option discussed with respect to stage 850 of method 800, mutatis mutandis.

[00239] As discussed with respect to method 800, also in 1700 the connectivity model may be continuously updated as new data is collected from different users.

[00240] It is noted that the connectivity model used in method 1700 may include both inquisitive statement collected from selection according to method 800 and collected according to method 1700.

[00241] Fig. 18 is a block diagram illustrating system 1800 for assisted information collection, in accordance with examples of the presently disclosed subject matter. System 1800 includes at least interface 1810, processor 1820 and tangible memory module 1830. As will be clear to a person having ordinary skill in the art, system 1800 may include many additional components (e.g. power supply, user interface, casing, and so on and so forth). For the sake of brevity and clarity of discussion, such components are not discussed in detail.

[00242] It is noted that optionally, system 1800 may be used as server 1110 discussed above. Every variation and optional implementation discussed with respect to server 1110 may be applied to system 1800, mutatis mutandis. Every variation and optional implementation discussed with respect to system 1800 may be applied to server 1110, mutatis mutandis. [00243] Tangible memory module 1830 (also referred to as memory module 1830 and as memory 1830) is operable to store a connectivity model which includes a database of inquisitive statements and of connection strength evaluations of connections between the inquisitive statements. For example, memory module 1830 may store connectivity model 900. The database of the connectivity model stored in tangible memory module 1830 includes at least a first inquisitive statement, a plurality of second inquisitive statements connected to the first inquisitive statement, and CSEs of the plurality of connection between the first inquisitive statement and each of the second inquisitive statements.

[00244] system 1800 includes interface 1810 for obtaining a selection, of each user out of a plurality of users which selected the first inquisitive statement, of one of the second inquisitive statements as a following inquisitive statement to the first inquisitive statement, out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement. Referring to the examples set forth with respect to the previous drawings, interface 1810 may execute stage 810 of method 800.

[00245] Processor 1820 is configured to execute the following:

(a) Determine for each connection out of the plurality of connections a CSE, based on the selections of the plurality of users.

(b) Write the determined CSEs to the connectivity model.

(c) Select, in response to selection of the first inquisitive statement by a new user, a selected set of inquisitive statements based on a plurality of CSEs out of the determined CSEs.

(d) Present the selected set of inquisitive statements to the new user.

[00246] Referring to the examples set forth with respect to the previous drawings, processor 1820 may execute stages 820, 830, 840 and 850 of method 800.

[00247] It will be clear to a person having ordinary skill in the art that system 1800 may be designed to execute any combination of one or more of the additional stages of method 800 which were discussed above. Some of these options are discussed below.

[00248] Optionally, the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

[00249] Optionally, interface 1810 may be operable to obtain a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and processor 1820 may further be operable to provide to the new user information associated by the connectivity database with the selected inquisitive statement. [00250] Optionally, interface 1810 may be operable to obtain multiple selections of multiple users of following inquisitive statements for more than one inquisitive statement, and processor 1820 may be operable to process the multiple selections to determine CSEs and to write the CSEs to the connectivity model for a plurality of inquisitive statement which includes the first inquisitive statement and at least one of the second inquisitive statements, thereby determining CSEs of different levels of connections with respect to the first inquisitive statement.

[00251] Optionally, interface 1810 may be operable to obtain for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; tangible memory module 1830 may be operable to store the sequence of selections; and processor may further be operable to: (a) analyze the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and (b) to present the at least three inquisitive statements simultaneously, in response to selection of the first inquisitive statement.

[00252] Optionally, tangible memory module 1830 may be is operable to store for at least one second inquisitive statement records of related activities by different users. That is, system 1800 may record on tangible memory module 1830, for each inquisitive statement out of multiple inquisitive statements (including at least one of the second inquisitive statements), activities of different users which are associated with the respective inquisitive statement (such activities are also referred to as "related activities", which are related to the respective inquisitive statement). Processor 1820 in such case may be operable to determine the CSE for the at least one second inquisitive statement further based on the records of the related activities.

[00253] Optionally, interface 1810 may further be useful for obtaining selection related parameters associated with each of the selections of the plurality of users, and processor 1820 may be operable to: process the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the CSE as a connection strength vector which includes at least two connection strength values, to select a subset of connection strength values based on user parameters of the new user, and to select the selected set of inquisitive statements based on the subset of connection strength values of each of the plurality of CSEs.

[00254] Reverting to method 800, it is noted that method 800 may be executed by a processor, which executes instructions which are stored on a non-transitory computer-readable medium. Stage 810 may include obtaining the selections by the processor from an interface (such as interface 1810, for example). For example, the non-transitory computer-readable medium may be a hard disk drive of server 1110, it may be tangible memory module 1830, it may be an optical storage medium (e.g. a CD or a DVD), and so on.

[00255] According to an aspect of the invention, a non-transitory computer-readable medium for assisted information collection is disclosed. The non-transitory computer-readable medium includes instructions stored thereon, that when executed on a processor, perform the steps of: (a) for a first inquisitive statement selected by a plurality of users, obtaining a selection of each user out of the plurality of users of a following inquisitive statement out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; wherein the set of optional inquisitive statements is selected for the user out of a plurality of second inquisitive statements associated with the first inquisitive statement by a connectivity model stored in a tangible memory module; (b) processing the selections of the plurality of users, to determine a connection strength evaluation for each connection out of a plurality of connections between the first inquisitive statement and a respective second inquisitive statement out of the plurality of second inquisitive statements; (c) writing the determined connection strength evaluations to the connectivity model; (d) in response to selection of the first inquisitive statement by a new user, selecting a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and (e) presenting the selected set of inquisitive statements to the new user.

[00256] It is noted that optionally, the instructions stored on the non-transitory computer-readable medium may include instructions for the execution by a processor of method 800. It will be clear to a person having ordinary skill in the art that the non-transitory computer-readable medium may further include additional instructions stored thereon that, when executed by the processor, perform a combination of one or more of the additional stages of method 800 which were discussed above, out of all such possible combinations. Some of these options are discussed below.

[00257] Referring to the non-transitory computer-readable medium, optionally the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

[00258] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: obtaining a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and providing to the new user information associated by the connectivity model with the selected inquisitive statement. [00259] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: repeating (a) the obtaining of selections, (b) the processing of the selections of the plurality of users to determine connection strength evaluations and (c) the writing of the connection strength evaluations to the connectivity model for one or more of the second inquisitive statements, thereby determining connection strength evaluations of different levels of connections with respect to the first inquisitive statement.

[00260] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: (a) executing the repeating for multiple levels of connections; (b) repeating the selecting of a selected set of inquisitive statements for each of a series of selecting by the new user of inquisitive statements out of selected sets of inquisitive statements, thereby exposing the new user to a group of inquisitive statements which are relevant to an objective of the user as selected by selecting the first inquisitive statement.

[00261] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the step of normalizing with respect to each other the connection strength evaluations of connections stemming from each second inquisitive statements out of the one or more second inquisitive statements.

[00262] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: (a) obtaining for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; and (b) storing the sequence of selections in a data base stored on a non- volatile memory storage.

[00263] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: (a) analyzing the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and (b) presenting the at least three inquisitive statements simultaneously, in response to selection of the first inquisitive statement.

[00264] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: recording for at least one second inquisitive statement activities of different users which are associated with the respective second inquisitive statement, and determining the connection strength evaluation for the at least one second inquisitive statement further based on the recorded activities.

[00265] Optionally, the non-transitory computer-readable medium further includes instructions stored thereon that when executed on the processor perform the steps of: obtaining selection related parameters associated with each of the selections of the plurality of users, processing the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the connection strength evaluation as a connection strength vector including at least two connection strength values, and selecting the selected set of inquisitive statements based on a subset of connection strength values of each of the plurality of connection strength evaluations, the subset being selected in response to user parameters of the new user.

[00266] Reverting to method 1000, it is noted that method 1000 may be executed by a processor, which executes instructions which are stored on a non-transitory computer-readable medium.

[00267] Reverting to method 1300, it is noted that method 1300 may be executed by a processor, which executes instructions which are stored on a non-transitory computer-readable medium.

[00268] Reverting to method 1700, it is noted that method 1700 may be executed by a processor, which executes instructions which are stored on a non-transitory computer-readable medium.

[00269] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

[00270] It will be appreciated that the embodiments described above are cited by way of example, and various features thereof and combinations of these features can be varied and modified.

[00271] While various embodiments have been shown and described, it will be understood that there is no intent to limit the invention by such disclosure, but rather, it is intended to cover all modifications and alternate constructions falling within the scope of the invention, as defined in the appended claims.

[00272] Although embodiments of the invention have been described by way of illustration, it will be understood that the invention may be carried out with many variations, modifications, and adaptations, without exceeding the scope of the claims.

Claims

What is claimed is:

A computer-implemented method for assisted information collection, comprising executing on a processor the steps of:

for a first inquisitive statement selected by a plurality of users, obtaining a selection of each user out of the plurality of users of a following inquisitive statement out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; wherein the set of optional inquisitive statements is selected for the user out of a plurality of second inquisitive statements associated with the first inquisitive statement by a connectivity model stored in a tangible memory module;

processing the selections of the plurality of users, to determine a connection strength evaluation for each connection out of a plurality of connections between the first inquisitive statement and a respective second inquisitive statement out of the plurality of second inquisitive statements;

writing the determined connection strength evaluations to the connectivity model; in response to selection of the first inquisitive statement by a new user, selecting a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and

presenting the selected set of inquisitive statements to the new user.

The method according to claim 1 , wherein the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

The method according to claim 1, further comprising obtaining a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and providing to the new user information associated by the connectivity model with the selected inquisitive statement.

The method according to claim 1, further comprising repeating the stages of obtaining selections, processing the selections of the plurality of users to determine connection strength evaluations and writing the connection strength evaluations to the connectivity model for one or more of the second inquisitive statements, thereby determining connection strength evaluations of different levels of connections with respect to the first inquisitive statement.

5. The method according to claim 4, wherein the repeating is executed for multiple levels of connections, wherein the method comprises repeating the selecting of a selected set of inquisitive statements for each of a series of selecting by the new user of inquisitive statements out of selected sets of inquisitive statements, thereby exposing the new user to a group of inquisitive statements which are relevant to an objective of the user as selected by selecting the first inquisitive statement.

6. The method according to claim 4, further comprising normalizing with respect to each other the connection strength evaluations of connections stemming from each second inquisitive statements out of the one or more second inquisitive statements.

7. The method according to claim 1, the method comprising obtaining for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; and storing the sequence of selections in a data base stored on a nonvolatile memory storage.

8. The method according to claim 7, further comprising:

analyzing the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and

in response to selection of the first inquisitive statement, presenting the at least three inquisitive statements simultaneously.

9. The method according to claim 1, further comprising recording for at least one second inquisitive statement activities of different users which are associated with the respective second inquisitive statement, wherein the determining of the connection strength evaluation for the at least one second inquisitive statement is further based on the recorded activities.

10. The method according to claim 1, wherein the obtaining further comprises obtaining selection related parameters associated with each of the selections of the plurality of users, wherein the processing comprises processing the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the connection strength evaluation as a connection strength vector comprising at least two connection strength values, wherein the selecting of the selected set of inquisitive statements is based on a subset of connection strength values of each of the plurality of connection strength evaluations, the subset being selected in response to user parameters of the new user.

11. A computer-implemented method for assisted information collection, comprising executing on a processor the steps of:

for each user out of a plurality of users, obtain search history which includes information of inquisitive statements used by the user with one or more web search system over at least one search duration of the user;

processing the plurality of search histories of the plurality of users, to determine connection strength evaluations for a plurality of directional connections between inquisitive statements used by the plurality of users;

writing the determined connection strength evaluations to a connectivity model; based on connection strength evaluations of the connectivity model and on a search history of a new user (the search history of the new user including at least one of the inquisitive statements of the connectivity model), selecting a selected set of inquisitive statements out of the inquisitive statement of the connectivity model; and

presenting the selected set of inquisitive statements to the new user.

12. A method for providing guidance to a user of a data network for obtaining required information regarding a user defined objective, comprising the steps of:

responsive to a request for guidance from each user out of plurality of users, the request being associated with an objective that is stored in a database, displaying to the user a list of questions/phrases and objectives that are connected to the objective and allowing the user to select questions/phrases out of the list of questions/phrases, wherein the database includes:

at least one user defined objective;

a plurality of questions/phrases of one or more words;

a model of connections comprising connections between questions/phrases and objectives, and connections between questions/phrases and other questions/phrases; storing the selections of each user and his personal navigation paths through the selected questions/phrases that lead to said selections;

assigning numerical strengths to each connection by aggregating information from the collection of paths of users out of the plurality of users that are associated with the same objective, in response to the popularity of usage of said connection among users; and displaying questions/phrases as continuation questions/phrases of other questions/phrases, based on the assigned strengths.

13. The method according to claim 12, further comprising allowing users to add questions/phrases and objectives to the database; and generating new connections in the database based on the added questions/phrases and objectives.

14. The method according to claim 13, further comprising dynamically updating strengths to at least one connection by repeating the stages of displaying, allowing, storing and assigning.

15. The method according to claim 12, wherein a connection is represented by a plurality of connection values associated with the at least one of the following parameters: (a) contextual parameters of the user; (b) geographical location of the user; (c) characterizing features of the user; and (d) physical or mental conditions of the user.

16. The method according to claim 12, wherein the database further comprises at least one connection of one or more targets to at least one question/phrase, where each target represents a link to related information defined by at least one user and strength is assigned to each connection by aggregating information from the collection of paths of all users or from segments thereof, that are associated with the same objective, and according to the popularity of usage of said connection among all users.

17. The method according to claim 12, wherein the database further comprises at least one promoted connection having biased strengths to questions/phrases and/or targets of the initial model.

18. A system for assisted information collection, the system comprising:

a tangible memory module, operable to store a connectivity model which comprises a database of inquisitive statements and of connection strength evaluations of connections between the inquisitive statements; wherein the database comprises at least a first inquisitive statement, a plurality of second inquisitive statements connected to the first inquisitive statement, and connection strength evaluations of the plurality of connection between the first inquisitive statement and each of the second inquisitive statements;

an interface for obtaining a selection, of each user out of a plurality of users which selected the first inquisitive statement, of one of the second inquisitive statements as a following inquisitive statement to the first inquisitive statement, out of a set of optional inquisitive statements presented to the user in response to his selection of the first inquisitive statement; and

a processor, configured to: (a) determine for each connection out of the plurality of connections a connection strength evaluation based on the selections of the plurality of users, (b) to write the determined connection strength evaluations to the connectivity model; (c) to select, in response to selection of the first inquisitive statement by a new user, a selected set of inquisitive statements based on a plurality of connection strength evaluations out of the determined connection strength evaluations; and (d) to present the selected set of inquisitive statements to the new user.

19. The system according to claim 18, wherein the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

20. The system according to claim 18, wherein the interface is operable to obtain a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, wherein the processor is further operable to provide to the new user information associated by the connectivity database with the selected inquisitive statement.

21. The system according to claim 18, wherein the interface is operable to obtain multiple selections of multiple users of following inquisitive statements for more than one inquisitive statement; wherein the processor is operable to process the multiple selections to determine connection strength evaluations and to write the connection strength evaluations to the connectivity model for a plurality of inquisitive statement which includes the first inquisitive statement and at least one of the second inquisitive statements, thereby determining connection strength evaluations of different levels of connections with respect to the first inquisitive statement.

22. The system according to claim 18, wherein the interface is operable to obtain for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; wherein the tangible memory module is operable to store the sequence of selections; wherein the processor is further operable to: (a) analyze the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and (b) to present the at least three inquisitive statements simultaneously, in response to selection of the first inquisitive statement.

23. The system according to claim 18, wherein the tangible memory module is operable to store for at least one second inquisitive statement records of related activities by different users, wherein the processor is operable to determine the connection strength evaluation for the at least one second inquisitive statement further based on the records of the related activities.

24. The system according to claim 18, wherein the interface is further for obtaining selection related parameters associated with each of the selections of the plurality of users; wherein the processor is operable to process the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the connection strength evaluation as a connection strength vector which comprises at least two connection strength values, to select a subset of connection strength values based on user parameters of the new user, and to select the selected set of inquisitive statements based on the subset of connection strength values of each of the plurality of connection strength evaluations.

25. A non-transitory computer-readable medium for assisted information collection, comprising instructions stored thereon, that when executed on a processor, perform the steps of:

presenting the selected set of inquisitive statements to the new user.

26. The non-transitory computer-readable medium according to claim 25, wherein the first inquisitive statement and the plurality of second inquisitive statements are natural language textual statements.

27. The non-transitory computer-readable medium according to claim 25, further comprising instructions stored thereon that when executed on the processor perform the steps of: obtaining a selection by the new user of an inquisitive statement out of the selected set of inquisitive statements, and providing to the new user information associated by the connectivity model with the selected inquisitive statement.

28. The non-transitory computer-readable medium according to claim 25, further comprising instructions stored thereon that when executed on the processor perform the steps of: repeating (a) the obtaining of selections, (b) the processing of the selections of the plurality of users to determine connection strength evaluations and (c) the writing of the connection strength evaluations to the connectivity model for one or more of the second inquisitive statements, thereby determining connection strength evaluations of different levels of connections with respect to the first inquisitive statement.

29. The non-transitory computer-readable medium according to claim 28, further comprising instructions stored thereon that when executed on the processor perform the steps of: (a) executing the repeating for multiple levels of connections; (b) repeating the selecting of a selected set of inquisitive statements for each of a series of selecting by the new user of inquisitive statements out of selected sets of inquisitive statements, thereby exposing the new user to a group of inquisitive statements which are relevant to an objective of the user as selected by selecting the first inquisitive statement.

30. The non-transitory computer-readable medium according to claim 28, further comprising instructions stored thereon that when executed on the processor perform the step of normalizing with respect to each other the connection strength evaluations of connections stemming from each second inquisitive statements out of the one or more second inquisitive statements.

31. The non-transitory computer-readable medium according to claim 25, further comprising instructions stored thereof that when executed by the processor perform the steps of: (a) obtaining for each user out of the plurality of users a sequence of selections of inquisitive statements by the user, the sequence defining a path between entries of different inquisitive statements in the connectivity model; and storing (b) the sequence of selections in a data base stored on a non- volatile memory storage.

32. The non-transitory computer-readable medium according to claim 31, further comprising instructions stored thereon that when executed on the processor perform the steps of: (a) analyzing the paths of the plurality of users to identify at least one frequently occurring path, the frequently occurring path identifying an ordered set of at least three inquisitive statements; and (b) presenting the at least three inquisitive statements simultaneously, in response to selection of the first inquisitive statement.

33. The non-transitory computer-readable medium according to claim 25, further comprising instructions stored thereon that when executed on the processor perform the steps of: recording for at least one second inquisitive statement activities of different users which are associated with the respective second inquisitive statement, and determining the connection strength evaluation for the at least one second inquisitive statement further based on the recorded activities.

34. The non-transitory computer-readable medium according to claim 25, further comprising instructions stored thereon that when executed on the processor perform the steps of: obtaining selection related parameters associated with each of the selections of the plurality of users, processing the selections of the plurality of users and the associated selection related parameters, to determine for each connection out of the plurality of connections the connection strength evaluation as a connection strength vector comprising at least two connection strength values, and selecting the selected set of inquisitive statements based on a subset of connection strength values of each of the plurality of connection strength evaluations, the subset being selected in response to user parameters of the new user.