RU2604725C2 - System and method for generating information on plurality of points of interest - Google Patents

Abstract

FIELD: information technology.

SUBSTANCE: invention relates to processing and providing the user with information on objects, namely to generation and presentation of information on multiple points of interest. Card of first interest point and card of second interest point are recieved on the server, each of cards includes a predetermined set of parameters describing the corresponding object, and obtaining from each card multiple parameters including location parameters and descriptive parameters. Then one performs calculation of quantitative magnitude proximity of the first and second points of interest, which indicates potential possibility of associating these points of interest, and in response to quantitative index of proximity excessing proximity threshold complex point of interest is created. Complex point of interest is assigned, at least partially, information from a data card of one of interest points, defined as the main point of interest.

EFFECT: technical result consists in more compact display of the most significant information, which provides the user with possibility of faster orientation in data aqusition.

24 cl, 4 dwg

Description

FIELD OF TECHNOLOGY

[1] The present technology relates to a system and method for generating information on a plurality of points of interest.

BACKGROUND

[2] In modern conditions, users are faced with an abundance of information that they receive from the Internet. Presenting all available information on the displays of client devices may not be the best solution due to the difficulty of perception.

[3] In the publication of patent application US 20130155181 A1, "Point of interest (poi) data positioning in image", authors teach clustering of points of interest that are displayed in a two-dimensional image. Thus, clustering of tags corresponding to a relatively sequential series of images is possible. In particular, clustering is possible depending on the level of image scale.

ESSENCE OF TECHNOLOGY

[4] The purpose of this technology is to eliminate or mitigate at least some of the inconveniences present in the art.

[5] In accordance with embodiments of the present technology, a method is provided for generating information about a plurality of points of interest and presenting said information to a user. Points of interest represent objects. The analysis of points of interest and associated information is carried out, and points of interest representing complex objects are determined, and points of interest that represent objects that are elements of this complex are determined. Next, a complex point of interest is created, information that is displayed to the user is associated with a complex point of interest. Although the information that is associated with the complex point of interest can be shown to the user as a mark on the map, this is not required. Information that is associated with a complex point of interest can be shown to the user in any form, for example, as a card of a complex object.

[6] In accordance with embodiments of the present technology, a method is provided for generating information about a plurality of points of interest and presenting said information to a user, the method comprising: obtaining a card of a first point of interest and a card of a second point of interest from a plurality of cards of points of interest, each of the cards of points of interest including itself a predefined set of parameters describing the corresponding object represented by the corresponding point of interest; obtaining a first plurality of parameters from a first card of a first point of interest, a first plurality of parameters including at least one location parameter and at least one descriptive parameter; obtaining a second plurality of parameters from a second card of a second point of interest, a second plurality of parameters including at least one location parameter and at least one descriptive parameter; based on the first set of parameters and the second set of parameters, calculating a quantitative measure of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest; in response to the quantitative proximity indicator exceeding the proximity threshold, creating a complex point of interest representing the first point of interest and the second point of interest, and creating a complex point of interest includes the following steps: (i) applying a heuristic to the first point of interest and second point of interest an algorithm for determining one of these points of interest as a primary point of interest, and for determining another point of interest as a secondary point of interest, (ii) obtaining from the storage device of the information card of the main point of interest; (iii) assigning to a complex point of interest, at least partially, information from the information card of the main point of interest.

[7] In some embodiments of the technology, the method further includes: receiving from the memory card cards of a secondary point of interest; Assigning to a complex point of interest at least a portion of at least one parameter from the card of a secondary point of interest.

[8] In some embodiments of the technology, the server generates a plurality of point of interest cards, wherein one point of interest card corresponds to one entity.

[9] In some embodiments of the technology, generating a plurality of point of interest cards includes receiving by the server information about objects that could potentially be represented by points of interest, including obtaining a predetermined set of parameters for each object from a plurality of objects, the predetermined set of parameters including at least one location parameter and at least one descriptive parameter, and assigning corresponding parameters to the corresponding point cards ENA.

[10] In some embodiments of the technology, obtaining information about objects that could potentially be represented by points of interest is carried out from open data sources.

[11] In some embodiments of the technology, obtaining information about objects that could potentially be represented by points of interest further includes evaluating the priority of the data sources, and obtaining at least a portion of the plurality of parameters of the corresponding potential point of interest from the data source that has the highest priority compared to other data sources.

[12] In some embodiments of the technology, a descriptive parameter is any of: name of the object, description of the object, photograph of the object, contact details, hyperlink to the site.

[13] In some embodiments of the technology, the predetermined set of parameters further includes an object significance parameter, and in which the heuristic algorithm for determining the determination of the main point of interest and the secondary point of interest takes into account the object significance parameter.

[14] In some embodiments of the technology, the significance parameter of an object is determined by determining its photorating.

[15] In some embodiments of the technology, a set of word significance markers is pre-programmed, and in which the heuristic algorithm for determining the determination of the main point of interest and secondary point of interest takes into account the word importance markers from the set of word significance markers.

[16] In some embodiments of the technology, the method further includes receiving a user request to provide him with information about any of: a first object and a second object and, in response to receiving this request, providing the user with information from a card of a complex point of interest.

[17] In some embodiments of the technology, the location parameter is determined taking into account a subparameter of geographical proximity and a subparameter of density of objects, and a subparameter of geographical proximity depends on the distance between objects, and a subparameter of density of objects depends on the number of objects per unit area.

[18] Another object of the present technology is a computer. The computer includes a processor. The processor configuration is configured so that the computer can: receive a card of the first point of interest and a card of the second point of interest from the set of cards of points of interest, each of the cards of points of interest includes a predetermined set of parameters describing the corresponding object represented by the corresponding point of interest; obtaining a first plurality of parameters from a first card of a first point of interest, a first plurality of parameters including at least one location parameter and at least one descriptive parameter; obtaining a second plurality of parameters from a second card of a second point of interest, a second plurality of parameters including at least one location parameter and at least one descriptive parameter; based on the first set of parameters and the second set of parameters, calculating a quantitative measure of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest; in response to the quantitative proximity indicator exceeding the proximity threshold, creating a complex point of interest representing the first point of interest and the second point of interest, and creating a complex point of interest includes the following steps: (i) applying a heuristic to the first point of interest and second point of interest an algorithm for determining one of these points of interest as a primary point of interest, and for determining another point of interest as a secondary point of interest, (ii) obtaining from the storage device of the information card of the main point of interest; (iii) assigning to a complex point of interest, at least partially, information from the information card of the main point of interest.

[19] In some embodiments of the computer, the configuration of the processor is configured so that the computer can further perform: receiving from the memory card a secondary point of interest; Assigning to a complex point of interest at least a portion of at least one parameter from the card of a secondary point of interest.

[20] In some embodiments of the computer, the processor configuration is configured so that the computer can generate multiple cards of points of interest, with one card of a point of interest corresponding to one object.

[21] In some embodiments of a computer, generating a plurality of point of interest cards includes receiving by a computer information about objects that could potentially be represented by points of interest, including obtaining a predetermined set of parameters for each object from a plurality of objects, the predetermined set of parameters including at least at least one location parameter and at least one descriptive parameter, and assigning corresponding parameters to the corresponding point of interest cards.

[22] In some embodiments of the computer, information about objects that could potentially be represented by points of interest is obtained from open data sources.

[23] In some embodiments of the computer, obtaining information about objects that could potentially be represented by points of interest further includes evaluating the priority of the data sources, and obtaining at least a portion of the plurality of parameters of the corresponding potential point of interest from the data source that has the highest priority over with other data sources.

[24] In some embodiments of the computer, a descriptive parameter is any of: the name of the object, the description of the object, a photograph of the object, contact information, a hyperlink to the site.

[25] In some embodiments of the computer, the predetermined set of parameters further includes an object significance parameter, and in which the heuristic algorithm for determining the determination of the main point of interest and the secondary point of interest takes into account the object significance parameter.

[26] In some embodiments of a computer, the significance parameter of an object is determined by determining its photorating.

[27] In some embodiments of a computer in which a set of word significance markers are pre-programmed, and in which a heuristic algorithm for determining the determination of a main point of interest and a secondary point of interest takes into account word importance markers from a set of word significance markers.

[28] In some embodiments of the computer, the processor configuration is configured so that the computer can additionally receive a user request to provide him with information about any of: the first object and the second object and, in response to receiving this request, provide the user with information from the card of a complex point of interest .

[29] In some embodiments of the computer, the location parameter is determined taking into account a subparameter of geographical proximity and a subparameter of the density of objects, and a subparameter of geographical proximity depends on the distance between the objects, and the subparameter of the density of objects depends on the number of objects per unit area.

[30] In the context of the description of the present technology, a “server” is a program running on appropriate equipment and capable of receiving requests (for example, provided by navigation devices) transmitted over the network and executing these requests or ensuring their execution. The equipment may be a single computer or a single computer system, however, neither one nor the other is mandatory in relation to the proposed technology. In this context, the term “server” does not mean that each task (for example, provided for by accepted instructions or requests) or any specific task will be accepted, completed or will be provided by the same server (that is, the same software and / or equipment); it is assumed that the reception and transmission, execution or enforcement of any task or request, or the processing of the results of a task or request, can be carried out by any number of software or device components, and all these software or equipment components can be represented by one server or several servers, the term " server ”covers both of these options.

[31] In the context of the description of the present technology, the term "information" includes information of any nature or type that can be recorded in a database. Thus, information covers, among other things, audiovisual information (images, video, audio, etc.), data (map data, location data, numerical data, etc.), text information (pointers, names, descriptions, warnings, text messages, etc.), documents, spreadsheets, etc.

[32] In the context of the description of this technology, the term "software component" covers software (corresponding to a specific hardware), which is both necessary and sufficient to perform a specific specified function (s).

[33] In the context of describing the present technology, the term “point of interest” (POI) refers to a mark on a map that identifies an object or group of objects. Points of interest may contain information about the object (s), for example, name, type, address, contact information.

[34] In the present description, the expression “storage medium intended for use by a computer” (also referred to as “storage medium”) encompasses storage media of any nature and type, including random access memory devices, read-only memory devices, disks (compact discs, DVDs, floppy disks, hard drives, etc.), USB keys, solid state drives, tape drives, etc.

[35] In the context of the description of this technology, a “database” is any structured data set, regardless of the particular structure, database management program or equipment on which data is stored, memory is implemented, or the data can be used in any other way. The database can be implemented on the same equipment as the process that stores or uses the information recorded in the database, or on separate equipment, such as a dedicated server or multiple servers.

[36] In the present description, the words “first”, “second”, “third”, etc. are used only as descriptive elements for the purpose of separating nouns that differ from each other, and not for the purpose of determining any specific relationship between these nouns. Thus, for example, it should be understood that the terms “first point of interest” and “third point of interest” do not mean the introduction of a specific sequence, type, chronology, hierarchy or ranking (for example) of a particular point of interest or several points of interest, but their use (itself per se) does not mean that in any particular situation there must necessarily exist some kind of “second point of interest”. In addition, as indicated in this description regarding other embodiments of the technology, a reference to the “first” element and the “second” element does not mean that two elements cannot actually represent the same element in the real world. Thus, for example, in some cases, the “first” server and the “second” server can be one component of software and (or) equipment, and in other situations can be implemented on various software and (or) equipment.

[37] Each of the technology implementation options has at least one of the above objectives and / or one of the above aspects, but not necessarily all of them. It should be borne in mind that some aspects of this technology that are the result of an attempt to achieve the aforementioned goal may not achieve this goal and / or may achieve other goals not specifically mentioned here.

[38] Additional and / or alternative features, objectives, aspects and advantages of this technology will become apparent from the following description, accompanying drawings, and the attached claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[39] For a better understanding of this technology, as well as its other aspects and features, it is proposed to refer to the following description, which should be used in conjunction with the accompanying drawings, in which:

[40] FIG. 1 is a schematic illustration of an embodiment of a networked computer system implemented in accordance with embodiments of the present technology without limiting its scope.

[41] FIG. 2 is a schematic representation of a map fragment generated by a server and displayed on a display of a client device (prior art).

[42] FIG. 3 is a schematic representation of a map fragment shown on a display of a client device generated by a server in accordance with embodiments of the present technology that do not limit its scope.

[43] FIG. 4 is a flowchart of a method 400 running on a server schematically depicted in FIG. 1, performed in accordance with embodiments of the present technology, not limiting its scope.

DETAILED DESCRIPTION

[44] In FIG. 1 is a schematic diagram of various computer systems 100 in communication with each other via a data network 110. It is important to keep in mind that various computer systems 100 are presented as an illustrative embodiment of the present technology. Thus, the following description thereof should be construed solely as a description of illustrative examples of the present technology. This description is not intended to determine the scope or scope of this technology. Some useful examples of modifications to computer systems 100 may also be covered by the following description. The purpose of this is also solely assistance in understanding, and not defining the scope and boundaries of this technology. These modifications are not an exhaustive list, and it will be understood by those skilled in the art that other modifications are possible. In addition, this should not be interpreted so that where it has not yet been done, i.e. where examples of modifications have not been set forth, no modifications are possible, and / or that what is described is the only way to implement this element of this technology. As will be clear to a person skilled in the art, this is most likely not the case. In addition, it should be borne in mind that computer systems 100 represent, in some specific manifestations, a fairly simple embodiment of the present technology, and in such cases is presented here in order to facilitate understanding. As will be clear to a person skilled in the art, many embodiments of the present technology will have much greater complexity.

[45] The system 100 includes a server 102. The server 102 may be a conventional computer server. In an example embodiment of the present technology, server 102 may be a Dell ™ PowerEdge ™ server that uses the Microsoft ™ Windows Server ™ operating system. Needless to say, the server 102 may be any other suitable hardware and / or application software and / or system software, or a combination thereof. In the present embodiment of the present technology, not limiting its scope, server 102 is a single server. In other non-limiting embodiments of the present technology, the functionality of the server 102 can be shared and can be performed using multiple servers.

[46] In this embodiment of the present technology, the server 102 is controlled and / or managed by a card service provider, such as, for example, a Yandex ™ card service provider. In alternative embodiments of the present technology, server 102 may have access to a card service provided by a third-party provider.

[47] Server 102 includes a storage medium 104 that may be used by the server. In principle, this storage medium 104 can be a medium of absolutely any type and nature, including RAM, ROM, disks (CDs, DVDs, diskettes, hard drives, etc.), USB flash drives, solid state drives, tape drives, etc., as well as their combinations.

[48] Embodiments of the server 102 are well known in the art. Thus, it is sufficient to note that the server 102 includes, inter alia, a network communication interface (for example, a modem, network card, and the like) (not shown) for two-way communication over a data network 110; and a processor (not shown) connected to a network communication interface that is configured to perform various procedures, including those described below. To this end, the processor may store or have access to computer-readable instructions stored on the storage medium 104, the execution of which the processor initiates, and may perform the various procedures described herein.

[49] The storage medium 104 of the server 102 is designed to store data, including machine-readable instructions and databases.

[50] In particular, the storage medium 104 of the server 102 stores databases 106 in which cartographic material and information about a plurality of objects marked with points of interest are stored on the cartographic material.

[51] In this embodiment of this technology, many objects are many attractions and points of interest for tourists in Moscow in the Russian Federation. For example, objects from this set of objects can be, for example, the Moscow Kremlin, the Bolshoi Theater, the Maly Theater, the Assumption Cathedral, the Archangel Cathedral, the lobby of the metro station Ploshchad Revolyutsii, and others.

[52] In other embodiments of the present technology, a plurality of objects may additionally or alternatively include other objects, for example, catering, and / or retail objects, and others. For example, it may be the Shopping and Entertainment Center "European", located at: Russia, Moscow, pl. Kievsky Station, 2. It can also be a gift shop "Red Cube", located at: Russia, Moscow, st. 1st Tverskaya-Yamskaya, 4. It could also be a Red Cube gift shop located in the Evropeisky shopping center.

[53] Objects are marked on the cartographic material as points of interest. A point of interest may be associated with a card of that point of interest.

[54] In embodiments of the present technology, a point of interest is a mark on the map that designates an object. Points of interest are associated with cards of points of interest, which may contain information about the object, for example, name, type, address, contact information.

[55] All points of interest can be categorized according to a specific classifier, which can be a single-level, two-level, or multi-level classifier.

[56] For example, a two-level classifier may include the following headings and subheadings (classifier elements that are subheadings are indicated in brackets): business and production (business centers, companies, industrial enterprises, other organizations), state and society (security, government agencies, emergency services, social institutions), culture (libraries and archives, exhibition centers, cinemas, concert halls, cultural centers, museums, galleries, religion, media, theaters), medical ina (pharmacies, hospitals, veterinary clinics, dispensaries, women's consultations, medical goods, medical centers, medical commissions, first-aid posts, optics, polyclinics, maternity homes, sanatoriums, dentistry, emergency rooms, other medical institutions), science and education (scientific institutions, education) , recreation (architectural attractions, natural attractions, entertainment, sports, tourism), trade (car shops, household goods, clothes and shoes, products, specialized stores, trade centers, electronics), transportation (air transport, road transport, water transport, railway transport, public transport), services (car services, consumer services, utilities, accommodation, restaurants, cafes, funeral services, other services, communications, exterior care, financial services, legal and insurance services), settlements (cottage villages, centers of settlements, garden associations) and others.

[57] Three-level and multi-level classifiers have a greater level of detail due to the creation of classifier elements of lower levels. So, for example, in a three-level classifier, all or some of the subtopics can be detailed. For example, the “entertainment” sub-heading of the “leisure” rubric may contain elements of a lower level classification, for example: water parks, attractions, billiards, bowling alleys, zoos, gambling establishments, cinemas, night clubs, parks, gardens, recreation centers, paintball, airsoft, beaches, entertainment centers, circuses, other entertainment. As another example, the subdivision “car dealerships” under the heading “trade” may contain elements of a lower level classification, for example: auto parts, car dealerships, motor showrooms, and other car dealerships.

[58] The point of interest card is a structured block of information describing the corresponding object from a plurality of objects. The point of interest card is created by the server 102 as a result of executing program instructions stored on the storage medium 104, and then loaded into the database 106.

[59] The point of interest card has a certain structure due to a predetermined set of information that, in the process of creating the point of interest card, the server 102 must collect and store the point of interest in the card. The structure of the point of interest card can also be determined by a set of parameters characterizing the corresponding object, which can be included in the point of interest card. For example, the set of information included in the card of the point of interest representing the object of trade may be different from the set of information included in the card of the point of interest representing the sights. In various embodiments of the present technology, the number of parameters contained in the point of interest card may vary.

[60] In the present embodiment of the present technology, each point of interest card includes three groups of parameters: location parameters, descriptive parameters, and object significance parameters.

[61] In alternative embodiments of the present technology, each point of interest card may include a different number and / or different set of parameter groups. For example, each card may contain parameters distributed in the following four groups: location parameters, descriptive parameters, object significance parameters, object category parameters. Categories of objects may include, for example, categories such as “attractions”, “catering points”, “objects of trade”, and the like.

[62] In this embodiment of the present technology, the location parameter is the geographical coordinates of the object. For example, the geographical coordinates of the Bolshoi Theater: 55 ° 45′37 ′ ′ N 37 ° 37′07 ′ ′ c. d.

[63] In alternative embodiments of the present technology, the location parameter may, as a non-limiting example, the address of the object. So, the address of the Bolshoi Theater is: Russia, Moscow, Theater Square, building 1. In some alternative embodiments of this technology, there may be more than one location parameter (for example, geographical coordinates and address).

[64] In this embodiment of the present technology, descriptive parameters are the name of the object, description of the object, photograph of the object, contact details, hyperlink to the site. So, for example, the point of interest card created for the Bolshoi Theater may contain the following descriptive parameters. Name: “Bolshoi Theater”. Description: “The State Twice Order of Lenin Academic Bolshoi Theater of the Russian Federation (Bolshoi Theater) or simply the Bolshoi Theater is one of the largest in Russia and one of the most significant opera and ballet theaters in the world. The complex of buildings of the theater is located in the center of Moscow on Theater Square. " Photography - photograph of the facade of the Bolshoi Theater. Contact information: "Tel .: +7 495 455-55-55." Hyperlink to the site: “https://ru.wikipedia.org/wiki/Bolshoi Theater”.

[65] In alternative embodiments of the present technology, descriptive parameters, additionally or alternatively, may be any other parameters describing the subject.

[66] In this embodiment of the present technology, an object's significance parameter is a significance parameter calculated based on photorating. The essence of the significance parameter calculated on the basis of photorating is based on the hypothesis that a significant number of photographs displaying an object posted on the Internet testifies to the interest of users in this object.

[67] The generation of object point cards is performed by the server 102. Initially, the server 102 can obtain information about the corresponding object from any available data source, including from an open data source. Under the open data sources should be understood any external data sources that are available for receiving by the server 102, including by receiving over the network 110 transmission from various hosting providers. For example, open data sources are various web pages and websites, including Internet encyclopedias (e.g. Wikipedia), social networking sites (e.g. Facebook), official site sites (e.g. the Bolshoi Theater website), photo hosting sites ( for example, the Flickr photo hosting site), the websites of tourism and catering service providers, any other web pages and websites.

[68] Generating a plurality of point of interest cards includes receiving server information about objects. In a significant number of cases, information about the same object can be contained in various sources. For example, if the server 102 receives information from the Internet, information about the object can be contained on many sites at the same time. In this case, the server 102 determines the priority of the source and obtains information about the object from the available source having the highest priority. The prioritization of data sources can be carried out in any suitable way. For example, the source with the highest priority can be recognized as the source that will be issued first in the Yandex search engine in response to a search query containing the name of the object. For example, in response to the search query “Assumption Cathedral Moscow”, the Yandex search engine returns the page “Assumption Cathedral (Moscow)” of the Wikipedia web encyclopedia.

[69] Alternatively or additionally, when searching for suitable pages, priority may be given, for example, primarily to web encyclopedias, secondly to official sites, and thirdly to other sites. In addition, when searching for information about objects of certain categories, the highest priority can be assigned to specialized sites. For example, when receiving information about Orthodox cathedrals, sobory.ru may be given priority.

[70] Having determined the most significant source of information about the object, the server 102 receives from this source the information necessary for entering the parameter or location parameters and descriptive parameters into the object’s point card. If the source with the highest priority does not contain the information necessary to fill in one or more parameters, the corresponding information can be obtained from sources of lesser importance following the source with the highest priority. In some embodiments of the present technology, information about an object to be included on a point card may also include specially aggregated information. For example, for a point of interest card representing the Starbucks Café, such specially aggregated information could include specially aggregated Coffeehouse information. This information can subsequently be used to form cards of complex points of interest.

[71] When determining the significance parameter based on photorating, the number of photos available on the Internet and available to the server 102 on which the object is captured can be taken into account. The more photos on the Internet on which the object is captured will be detected by the server 102, the higher will be the rating of the corresponding object. The rating increase can be directly proportional to the number of identified photos, or it can be expressed by a function that takes into account other various factors, and where the rating increase is not directly proportional to the number of photos found on which the object is captured.

[72] The search and retrieval of photographs available on the Internet, on which the object is captured and which could potentially be found by the server 102, can be carried out in any suitable way.

[73] In alternative embodiments of the present technology, the significance parameters, additionally or alternatively, may be any other parameters describing the significance of the object. For example, other parameters of the significance of the object can be calculated on the basis of estimates of various users, which were given by users to the corresponding objects on certain resources on the Internet.

[74] Information about the objects stored in the databases 106 on the storage medium 104 of the server 102 may be stored in the form of cards of points of interest and cards of complex points of interest.

[75] The storage medium 104 of the server 102 also stores computer-readable instructions for managing the databases 106, updating, updating, updating them. In particular, machine-readable instructions stored on the storage medium 104 allow the server 102 to receive (update) information about objects on the data network 110, to store information about objects, including their points of interest, in databases 106, to change the description of the position and / or characteristics of these objects, delete the specified objects from the map by deleting such objects from the databases 106. In particular, the execution of machine-readable instructions makes it possible for server 102 to obtain information about objects rye potentially be represented by points of interest, including receiving a predetermined set of parameters of each object of the plurality of objects, wherein the predetermined set of parameters may include at least one location parameter and the at least one parameter descriptive. The execution of these machine-readable instructions also allows the server 102 to assign the appropriate parameters to the respective point of interest cards and save the point of interest cards in the databases 106.

[76] Machine-readable instructions stored on the storage medium 104 allow the server 102 to obtain information about objects that could potentially be represented by points of interest from open data sources.

[77] Alternatively or additionally, machine-readable instructions stored on the storage medium 104 allow the server 102 to obtain information about objects that could potentially be represented by points of interest from their own data sources. For example, the owner of the server 102 can independently determine the geographical coordinates of objects — sights within the city of Moscow — on the ground, and independently enter the received data into the cards of the points of the objects and save the data in databases 106.

[78] Alternatively or additionally, machine-readable instructions stored on the storage medium 104 allow the server 102 to receive information about objects that could potentially be represented by points of interest from the publisher, that is, a person interested in posting information about the object. For example, the server 102, which is under the control and / or management of a card service provider, can provide an opportunity for anyone to mark objects on maps and make a description of the corresponding objects. For example, such a person may be publisher 111, who connects to the map service from the electronic device 112 using the browser 116, downloads from the server 102 to the electronic device 112 to display on the display 118 a map of a certain area, marks on the map displayed on the display 118, the newly opened art gallery, indicates its name, gives a brief description and indicates contact details.

[79] The storage medium 104 of the server 102 also stores machine-readable instructions that enable the user 120 to receive from the client device 122 via the data transmission network 110 to provide a list of objects contained in a particular area of space, to receive information about objects stored from the database 106 in the databases 106 corresponding to the piece of space that the user 120 is interested in, and transmit this list to the client device 122 of the user 120 over the data transmission network 110 x, and also transmit to the client device 122 by user 111 to the network 110 for data transfer instructions displayed on the display 128 of the client device 122 of one or more points of interest and / or complex of points of interest on the map.

[80] In this embodiment of the present technology, server 102 may be configured to perform one or more searches in response to a search query (including a map service) entered by user 120 into browser 126 of client device 122 connected to server 102 via network 110 data. The server 102 is also configured to transmit to the client device 122 a search result that will be displayed to the user 120 of the client device 122 on the display 128 through the browser interface 126. These functions are well known in the art and therefore will not be described here.

[81] Server 102 is connected to a data network 110 via a communication line (not numbered). In some non-limiting embodiments of the present technology, the communication data network 110 may be the Internet. In other embodiments of the present technology, the data network 110 may be implemented differently — as a global data network, a local data network, a private data network, or the like.

[82] The implementation of the communication line is not limited and will depend on which devices are connected to the data network 110. By way of example, but not limitation, the connection of the server 102 to the communication transmission network 110 can be carried out via wired communication (Ethernet based connection). At the same time, other devices can be connected in other ways. So, in cases in which the connected device is a wireless communication device (for example, an electronic device 112 implemented as a smartphone), the connection is a wireless communication network (for example, inter alia, a 3G network link, a 4G network link, wireless Internet Wireless Fidelity or shortly WiFi®, Bluetooth®, etc.). In those examples where the device is a desktop computer (such as electronic device 112), the communication line can be either wireless or wired (Ethernet-based connection).

[83] It is important to keep in mind that various embodiments of the server 102, electronic device 112, communication lines for connecting to data network 110 are for illustrative purposes only. Thus, those skilled in the art will be able to understand the details of other specific embodiments of the server 102, electronic device 112, communication lines for connecting to a data network 110. Thus, the examples presented here do not limit the scope of the present technology.

[84] Through the data transmission network 110, the server 102 may be connected to the electronic device 112. The electronic device 112 is usually associated with the publisher 111. The publisher 111 is a person who posts information about objects having spatial coordinates to further provide access to them to the user 120. Among several non-limiting examples of publishers 111, among the many possible examples, we can name: (a) the owner of the newly opened art gallery, placing the coordinates, description and opening hours of the gallery in gray hanging two-dimensional maps (implemented on server 102), for example, on two-dimensional Yandex.Maps; (b) the administration of the museum, marking the name, coordinates, address, opening hours and description of the museum on a two-dimensional map service (implemented on server 102), for example, on two-dimensional Yandex.Maps.

[85] The options for electronic device 112 are not particularly limited, but personal computers (desktop computers, laptops, netbooks, etc.), wireless communication devices (mobile phones, smartphones, tablets, etc.) can be used as an example of electronic device 112. .), as well as network equipment (routers, switches or gateways). Depicted in FIG. 1 electronic device 112 is implemented as a Dell Precision T1700 MT personal computer CA033PT170011RUWS with an Intel® Xeon ™ processor, processor frequency: 3300 MHz, with an nVIDIA Quadro K2000 graphics card, with installed and running Windows 7 Pro 64-bit operating system.

[86] The electronic device 112 includes a storage medium 114 that can be used by a computer. In principle, this storage medium can be a carrier of absolutely any type and nature, including RAM, ROM, disks (CDs, DVDs, diskettes, hard drives, etc.), USB flash drives, solid state drives, drives on magnetic tape, etc., as well as their combinations. In the electronic device 112, schematically depicted in FIG. 1, the storage medium is implemented as a hard disk with 500 Gb of memory. The storage medium 114 may store user files and program instructions. In particular, the storage medium may store software for use in the browser 116. In this embodiment of the present technology, the browser 116 is implemented as Internet Explorer 11 for Windows 7. In general, the purpose of the browser 116 is to enable the publisher 111 to download files via the transmission network 110 data to the server 102.

[87] The implementation of browser 116 for downloading files is not particularly limited. In other non-limiting embodiments of the present technology, the browser 116 may be a Yandex browser, a Google Chrome browser, and others. It is important to keep in mind that any other commercially available or proprietary application can be used to implement embodiments of the present technology that do not limit its scope.

[88] The electronic device 112 is connected to a data network 110 via a communication line (not numbered).

[89] Through the data transmission network 110, the server 102 is also connected to the client device 122. The client device 122 is usually connected to the user 120. The user 120 is a person interested in receiving information about objects having spatial coordinates. Such objects may be objects, information about which was received by the server 102 from their own data sources, and / or from open data sources, and / or information about which was transmitted to the server 102 by the publisher 111 using the electronic device 112 by downloading such objects using a browser 116 over a data network 110. In this embodiment of the present technology, user 120 is a tourist using a client device 122 to search for attractions in the center of Moscow.

[90] In alternative embodiments of the present technology, a user may search for objects of a different category. For example, as a few non-limiting examples of users 120, among the many possible examples, we can name: (a) a tourist, using client device 122, searching for sights in the center of Moscow; (b) a buyer who is looking for a gift and souvenir shop in the area of the Kiev railway station in Moscow; c) a user who is looking for a cafe or restaurant nearby.

[91] It should be noted that the fact that the client device 122 is connected to the user 120 does not imply any particular mode of operation, nor does it need to be logged in, registered, or the like.

[92] The options for client device 122 are not particularly limited, but personal computers (desktop computers, laptops, netbooks, etc.), wireless devices (mobile phones, smartphones, tablets, etc.) can be used as an example of client device 122. .), as well as network equipment (routers, switches or gateways). Schematically depicted in FIG. 1 client device 122 is implemented as an Apple iPhone 5S smartphone with iOS 7 installed on it and the current operating system, with Bluetooth, Wi-Fi, 3G, LTE, GPS and GLONASS positioning systems.

[93] The client device 122 also includes a storage medium 124. In principle, this storage medium can be a medium of absolutely any type and nature, including RAM, ROM, disks (CDs, DVDs, diskettes, hard disks, etc.). .d.), USB flash drives, solid state drives, tape drives, etc., as well as combinations thereof. In the client device 122, schematically depicted in FIG. 1, the storage medium 124 is implemented as a 16 GB flash drive.

[94] The storage medium 124 may store user files and program instructions. In particular, the storage medium 124 may store software that implements the functions of the browser 126. In general, the purpose of the browser 126 is to enable the user 120 to upload files to the client device 122 via the data transfer network 110 from the server 102 and display the downloaded images (video) on display 128. The implementation of browser 126 is not specifically limited. As non-limiting examples, such browsers may be Yandex browser, Google Chrome, Internet Explorer, various mobile search applications and so on. In client device 122, browser 126 is implemented as a Yandex mobile browser. It is important to keep in mind that any other commercially available or proprietary application can be used to implement embodiments of the present technology that do not limit its scope.

[95] Alternatively or additionally, the storage medium 124 may store software specifically designed to display consolidated information about objects of certain categories of interest to the user. In such embodiments of the present technology, the demonstration of consolidated information about objects of certain categories can be carried out in any way, including on a map or not on a map, in the form of text and / or other visual elements.

[96] The client device 122 also includes a display 128, which is a 4 ″ touch screen with a resolution of 640 × 1136, which allows video information to be presented to the user 120, and which can also be used as an input device. Thus, the user 120 is able to see various objects, for example, points of interest on the map, or textual information about points of interest, on the display 128 in the browser interface 126 of the client device 122. In addition, the user 120 may make requests for information about objects by entering a request using the touch screen.

[97] FIG. 2 is a schematic diagram of a fragment of a card 200 generated by the server 102 and displayed on the display 128 of the client device 122 (prior art).

[98] In this example, a fragment of the map 200 with the objects on them in the form of marks on the map was created by the server 102 in response to a request from user 120 to provide him with a list of attractions located near user 120. Server 102, having received a request from user 120 from a client device 122, and having determined that the client device 122 is located in close proximity to the exit from the Okhotny Ryad metro station (point 202), it extracts the corresponding map fragment from the databases 106 and marks objects on it, found s as a result of the search. These operations performed by the server 102 are well known in the art and therefore will not be described further.

[99] As a result of processing user request 120, server 102 formed a map fragment with the following objects indicated on the map fragment: Moscow Kremlin (point 203), Assumption Cathedral (point 204), Arkhangelsk Cathedral (point 206), Bolshoi Theater (point 208) , Maly Theater (point 210).

[100] The user 120 may click on the display 118 on any of the objects. For example, he can click on point 204, representing the Assumption Cathedral. In response, the user may be shown a card 212 containing information about the Assumption Cathedral. In some embodiments of the present technology, the card 212 of the point 204 can be displayed automatically without clicking the user 120 at the point 204. In some embodiments of the present technology, only the card 304 of the complex point of interest 302 will be shown. In some embodiments of the present technology, server 102 determines the optimal number of point of interest cards and / or complex point of interest cards to be shown on display 108. For example, this may be determined so that card images do not overlap on display 108.

[101] FIG. 3 is a schematic representation of a fragment of a card 300 shown on a display 128 of a client device 122 formed by a server 102 in accordance with non-limiting embodiments of the present technology.

[102] In this example, a fragment of the map 300 with the objects located on them in the form of marks on the map was generated by the server 102 in response to a request from user 120 to provide him with a list of points of interest located near user 120. Server 102, having received a request from user 120 from client devices 122, and having determined that the client device 122 is located in close proximity to the exit from the Okhotny Ryad metro station (point 202), it extracts the corresponding map fragment from the databases 106 and marks objects on it, find flagged by the search. In this case, the server 102 as a result of a search identical to the search described above in the description of FIG. 2, will find the same objects, namely: Assumption Cathedral, Arkhangelsk Cathedral, Bolshoi Theater, Maly Theater. Up to this point, the operations performed by the server 102 are well known in the art.

[103] Next, the server 102 receives the point of interest cards, each of the point of interest cards includes a predetermined set of parameters describing a corresponding object represented by a corresponding point of interest. In this case, the objects represented by points of interest are the Moscow Kremlin, the Assumption Cathedral, the Archangel Cathedral, the Bolshoi Theater, and the Maly Theater.

[104] Then, the server 102 obtains a plurality of parameters from each point of interest representing the corresponding object, and calculates a quantitative indicator (or quantitative indicators) of the found points of interest indicating the potential for associating some of these points. In response to the excess of one (or several) quantitative indicators of the potential proximity of the proximity threshold value, the server 102 creates a complex point of interest (or several points of interest).

[105] As a result of this operation, the server 102 in this embodiment of the present technology forms a fragment of a map 300 with the following objects indicated on a fragment of a map 300: Bolshoi Theater (point 208), Maly Theater (point 210), Moscow Kremlin (point 302, indicated Fig. 3 rhombus). The Moscow Kremlin facility in this embodiment of this technology is represented by a complex point of interest.

[106] Point 302 is a complex point of interest. When you click on this point on the display 128 of the client device 122, the user 120 will be shown a card 304 of a complex point of interest - the Moscow Kremlin, which may also include brief information about the Moscow Kremlin itself (information 306), as well as about objects that are elements of the historical museum complex of the Moscow Kremlin, namely: about the Assumption Cathedral (information 308) and the Archangel Cathedral (information 310). Next to the information 308 and 310 there are arrows (not numbered), showing the user that by clicking on these arrows he will be shown additional information. In alternative embodiments of the present technology, a complex point of interest card 304 may include information about a primary object at a complex point of interest in the form of previously specially aggregated information, which may or may not include information about primary and secondary objects. For example, in cases when the card of a complex point of interest “Coffee Shops” is previously saved, such a point of interest may not contain specific information about either the main point of interest or secondary points of interest, or it may contain information about secondary points of interest, for example, about a cafe Starbucks, the Shokoladnitsa cafe and the Coffee House cafe, located in close proximity to each other.

[107] Similar operations carried out by the server 102 with respect to another category of points of interest (with respect to trading objects) will be described in more detail in the description of the flowchart of the method 400 executed on the server 102, schematically shown in FIG. 1, performed in accordance with embodiments of the present technology, not limiting its scope.

[108] FIG. 4 is a flowchart of a method 400 running on a server 102 of FIG. 1, performed in accordance with embodiments of the present technology, not limiting its scope.

[109] The method 400 begins at step 402, in which the server 102 obtains a card of the first point of interest and a card of the second point of interest from the set of cards of points of interest, each of the cards of points of interest includes a predetermined set of parameters describing a corresponding object represented by a corresponding point interest.

[110] Step 402 may be preceded by the receipt by the server 102 of the data transmission network 110 from the client device 122 of a user 120 request located in Moscow in the vicinity of the Okhotny Ryad metro station (point 202 in Fig. 2 and Fig. 3) to provide him information about objects of interest to tourists located within walking distance. As a result of a search at the request of user 120, server 102 can find in the immediate vicinity of user 120 the Moscow Kremlin (point 203 in Fig. 2), the Assumption Cathedral (point 204 in Fig. 2), the Archangel Cathedral (point 206 in Fig. 2 ), The Bolshoi Theater (point 208 in Fig. 2) and the Maly Theater (point 210 in Fig. 2).

[111] Server 102 receives cards of points of interest corresponding to the Assumption Cathedral (point 204 in Fig. 2), the Archangel Cathedral (point 206 in Fig. 2), the Bolshoi Theater (point 208 in Fig. 2), the Maly Theater (point 210 on Fig. 2) and the Moscow Kremlin (point 203 in Fig. 2). Cards of points of interest corresponding to these objects were previously generated by the server 102.

[112] Next, method 400 proceeds to step 404.

[113] Step 404 - obtaining a first set of parameters from a first card of a first point of interest, a first set of parameters including at least one location parameter and at least one descriptive parameter, and obtaining a second set of parameters from a second card of a second point of interest, a second set parameters, including at least one location parameter and at least one descriptive parameter.

[114] At step 404, the server 102 obtains a plurality of parameters from the points of interest cards that correspond to the objects found by the server 102 in response to the search query of the user 120. In this embodiment of the present technology, when the user 120 makes a request to provide him with a list of attractions in the vicinity of the user 120 located in the immediate vicinity of the exit from the Okhotny Ryad metro station (point 202), the server 102 obtains many parameters from the cards of points of interest, respectively the following objects: Assumption Cathedral (point 204 in Fig. 2), Arkhangelsk Cathedral (point 206 in Fig. 2), Bolshoi Theater (point 208 in Fig. 2 and Fig. 3), Maly Theater (point 210 in Fig. 2). 2 and in Fig. 3), and the Moscow Kremlin (point 203 in Fig. 2).

[115] As can be seen from the above example, there can be more than two cards of points of interest received by the server if more than two objects were received as a result of the search performed by the server 102. In such cases, each point card of any of the objects can be considered either the first card of the point of the object or the second card of the point of the object. Thus, the server 102 extracts a plurality of parameters from each card, while at this stage not knowing whether the corresponding card is the first object point card or the second object point card.

[116] Next, method 400 proceeds to step 406.

[117] Step 406, based on the first set of parameters and the second set of parameters, calculating a quantitative measure of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest.

[118] At step 406, the server 102, based on the first set of parameters and the second set of parameters, calculates a quantitative indicator of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest.

[119] A quantitative proximity indicator is a numerical indicator that indicates the potential presence of a relationship between objects. Objects will be considered interconnected when the quantitative proximity indicator of all objects exceeds a predefined threshold proximity value.

[120] In the simplest case, two objects will be compared. In this case, it will matter if the quantitative indicator of the proximity of these two objects exceeds the predefined threshold proximity value.

[121] In the case when more than two objects are compared, a quantitative proximity indicator can be calculated for each pair of objects from the group of objects, which can potentially be interdependent. In the case when the interdependence of one object with several other objects is established, all these objects can be recognized as interdependent.

[122] The calculation of a quantitative proximity indicator is performed by the server 102. In this case, various parameters can be taken into account, and each parameter can be assigned a different weight in the calculation. In this embodiment of the present technology, two groups of parameters are used to calculate a quantitative proximity indicator: a) a location parameter (including a subparameter of geographical proximity and a subparameter of an object density parameter, and b) a descriptive parameter that is a text proximity parameter.

[123] A subparameter of geographic proximity refers to a parameter that reflects the distance between objects. The meaning of this parameter is that interconnected objects are usually located close to each other. Accordingly, the parameter of geographical proximity can with high probability indicate that the objects are not interdependent (for example, the Assumption Cathedral in Moscow and the Assumption Cathedral in Vladimir are located at a distance exceeding 185 kilometers from each other, which may indicate the absence of communication between them). Thus, the parameter of geographical proximity includes a predetermined threshold value, above which objects will not be considered close enough to each other and, therefore, cannot be considered interrelated.

[124] A subparameter of object density refers to a correction parameter applied to the parameter of geographical proximity. The density parameter of objects reflects the number of objects of a certain category (for example, attractions) in a certain territory. The higher the density of objects in the corresponding territory, the more stringent requirements will be imposed on the geographical proximity of objects. That is, the severity of the parameter of geographical proximity is inversely proportional to the parameter of density of objects. For example, in the Central Administrative District of Moscow there are many attractions. Therefore, the density parameter of objects is quite high. As a result of applying this parameter, the value of the parameter of geographical proximity will decrease. Thus, the proximity of the Bolshoi Theater and the Maly Theater in Moscow will not be as significant as in areas where the number of objects of the same category is insignificant. On the contrary, in areas where the number of objects of a certain category is relatively small in a certain territory, objects relatively distant from each other can be recognized as interconnected objects. For example, on the Yucatan Peninsula in Mexico, there are such tourist attractions as cenotes, that is, natural dips formed from the collapse of the arches of limestone caves in which groundwater flows. Given the density of attractions in the respective territories, several cenotes could be considered interconnected objects, even if they were relatively wide apart from each other within a radius of 10 km.

[125] A descriptive parameter (text proximity parameter) is a parameter that is calculated taking into account the text proximity of object descriptions. When calculating the text proximity, the presence of a reference to another object in the text describing the object is taken into account. For example, the descriptive parameter from the point card of the object related to the Assumption Cathedral may contain the text “Assumption Cathedral of the Moscow Kremlin”, that is, mention the Moscow Kremlin. In turn, the descriptive parameter from the object’s point card related to the Moscow Kremlin may contain the text “The first to build the new Assumption Cathedral, because the old one built by Ivan Kalitoy, by that time was already very dilapidated,” that is, to mention the Assumption Cathedral. Thus, the description of each of these two objects mentions another object, which, taking into account the parameters of geographical proximity and the density parameter, can entail the server 102 determining a high quantitative indicator of proximity to pairs of objects of the Moscow Kremlin - Assumption Cathedral, and the Moscow Kremlin - Arkhangelsk Cathedral.

[126] Using the above method, server 102 can also determine that the quantitative indicator of proximity of the following pairs of objects is low: Bolshoi Theater - Maly Theater, Bolshoi Theater - Moscow Kremlin, Bolshoi Theater - Arkhangelsk Cathedral, Bolshoi Theater - Assumption Cathedral, Maly Theater - Moscow Kremlin, Maly Theater - Assumption Cathedral, Maly Theater - Arkhangelsk Cathedral. It should be understood that a quantitative proximity indicator can be calculated both for pairs of objects, and, alternatively, for large groups of objects.

[127] Next, method 400 proceeds to step 408.

[128] Step 408, in response to a quantitative proximity indicator exceeding the proximity threshold, creating a complex point of interest representing a first point of interest and a second point of interest.

[129] At step 408, the server 102 creates a complex point of interest. A complex point of interest represents a first point of interest and one or more second points of interest. A complex point of interest is created when a quantitative indicator of the proximity of the first point and the second point exceeds a predefined threshold value. In some cases, there may be several second points of interest, and then a complex point of interest represents the first point of interest and several second points of interest. For example, when a quantitative indicator of the proximity of a pair of Moscow Kremlin - Assumption Cathedral objects exceeds a threshold value of proximity, and when a quantitative indicator of the proximity of a pair of Moscow Kremlin - Archangel Cathedral objects also exceeds a threshold proximity value, a complex point of interest can be created that represents all three points of interest, one of which is the first point of interest, and the other two are secondary points of interest.

[130] One of the points of interest is the main point of interest. One or more other points of interest are secondary point (s) of interest.

[131] A complex point of interest is a point of interest, which includes information about the main point of interest, and may also include information about one or more minor points of interest. A complex point of interest is a point of interest that will be shown to the user 120 instead of the main point of interest and a secondary point of interest (or several secondary points of interest). The first point of interest, which is the main point of interest, is a point of interest representing a complex object, which includes objects that are part of a complex object. The second point of interest, which is a secondary point of interest, is the point of interest representing the object that is part of the complex object. For example, the “Evropeisky” shopping center includes many trading objects, one of which is the “Red Cube” gift and souvenir shop. Correspondingly, the Evropeisky shopping center can potentially be represented by a complex point of interest, which is the main point of interest, and the Red Cube gift and souvenir shop can be represented by a secondary point of interest, as well as other retail outlets located in the Evropeisky shopping center. In alternative embodiments of the present technology, a complex point of interest card may include information about a primary object at a complex point of interest in the form of previously specially aggregated information, which may or may not include information about primary and secondary objects. For example, in cases when the card of a complex point of interest “Shopping and entertainment center” is previously saved, such a point of interest may not contain specific information about either the main point of interest or secondary points of interest, or it may contain information about secondary points of interest, for example , about the Red Cube souvenir and gift shop located in it and The Body Shop, located in close proximity to each other.

[132] In this embodiment of the present technology, server 102, having determined between which pairs of objects the quantitative proximity indicator exceeds a threshold proximity value, applies a heuristic algorithm to such pairs of objects to identify the main point of interest and secondary points of interest.

[133] The construction of a heuristic algorithm is possible by the method of machine learning. In particular, the method of deductive training can be applied, which involves formalizing the knowledge of experts and transferring them to the server 102 as a knowledge base that can be stored on the storage medium 104 of the server 102. For example, many terms or pairs of terms or groups of terms can be created, defining the mutual hierarchy of these terms. For example, the following terms can be hierarchically ordered, in decreasing order of importance, as follows: Kremlin - Ensemble - Complex - Lavra - Cathedral - Church - Chapel - Icon. As will be appreciated by those skilled in the art, a large number of hierarchically related sets of terms may be stored on the server 102, indicating their hierarchical position within the set.

[134] In alternative embodiments of the present technology, the construction of a heuristic algorithm is possible through case studies or inductive training based on the identification of patterns in empirical data. In this case, the server 102, which is an intelligent system, is preliminarily presented with a set of positive and negative examples associated with any previously unknown regularity. In response, the server 102 generates decisive rules by which a plurality of examples are divided into positive and negative. The quality of the separation, as a rule, is then checked by an examination sample of examples.

[135] In this embodiment of this technology, as mentioned above, server 102 determined a high quantitative indicator of proximity to pairs of objects of the Moscow Kremlin - Assumption Cathedral and the Moscow Kremlin - Arkhangelsk Cathedral. Thus, if both proximity indicators (for the Moscow Kremlin - Assumption Cathedral pair and for the Moscow Kremlin - Arkhangelsk Cathedral pair) are exceeded, a heuristic algorithm will be applied to both pairs to determine the main point of interest and secondary point of interest in this pair of objects. In this case, based on several sets of hierarchically ordered terms (including the terms Kremlin - Ensemble - Complex - Cathedral - Church - Chapel - Icon), server 102 will determine that in each of the pairs of objects - Moscow Kremlin - Assumption Cathedral, and Moscow Kremlin - Arkhangelsk Cathedral, the main object is the Moscow Kremlin. Thus, the Moscow Kremlin is represented by the first point of interest, which is the main point of interest, and the Assumption Cathedral and the Archangel Cathedral are the second points of interest, that is, secondary points of interest.

[136] By defining a point of interest representing the Moscow Kremlin as the main point of interest (first point of interest), server 102 creates a complex point of interest representing the first point of interest and two second points of interest representing the Assumption Cathedral and the Archangel Cathedral. To this end, the server 102 receives from the information carrier 104 an information card of the first point of interest as the main point of interest (i.e., an information card containing information about the Moscow Kremlin) and assigns to the complex point of interest, at least partially, information from the information card of the main point of interest. Thus, a complex point of interest is assigned, at least partially, information from an information card relating to the Moscow Kremlin. Thus, this complex point can be assigned the name, geographical coordinates and a brief description of the Moscow Kremlin. It is possible, but not necessary, in a brief description that the Moscow Kremlin is an architectural and historical complex that includes the Assumption and / or Arkhangelsk Cathedrals. However, there may not be such a mention. The presence or absence of mention in this case will depend on whether these objects are mentioned in the description of the Moscow Kremlin contained in the main card of the point of interest.

[137] In alternative embodiments of the present technology, the method may further include retrieving from the storage medium, which is the storage medium 104, one or more cards of a secondary point of interest, and assigning the complex point of interest to at least a portion of at least one a parameter from one or more cards to a secondary point of interest. If we turn to the above example, then such two minor cards of points of interest can be cards of points of interest related to the Assumption Cathedral and the Archangel Cathedral. Thus, the complex point can be assigned the name, geographical coordinates and a brief description of the Moscow Kremlin, as well as an additional brief description of the Assumption Cathedral, as well as a brief description of the Archangel Cathedral.

[138] Within the framework of the present description, it should be understood that wherever it is indicated that data is received from any client device and / or from any mail server and / or from any other server, the receipt of electronic or other signal from the corresponding client device (server mail server), and the display on the device’s screen can be implemented as giving a signal to the screen, which contains certain information, which in the future can be interpreted by certain images and at least th least partially displayed on the screen of the client device. The supply and receipt of a signal are not always indicated in the framework of the present description to simplify the presentation and facilitate understanding of the present solution. Signals can be transmitted by optical methods (via fiber-optic communication, for example), electronic methods (by wire or wireless), mechanical methods (transmission of pressure, temperature and / or other physical parameters by which a signal can be transmitted).

Claims (24)

1. A method for generating information about a plurality of objects represented by a plurality of points of interest and presenting said information to a user, implemented on a server, including:
obtaining a card of a first point of interest and a card of a second point of interest from a plurality of cards of points of interest, each of the cards of points of interest includes a predetermined set of parameters describing a corresponding object represented by a corresponding point of interest;
obtaining a first plurality of parameters from a first card of a first point of interest, a first plurality of parameters including at least one location parameter and at least one descriptive parameter;
obtaining a second plurality of parameters from a second card of a second point of interest, a second plurality of parameters including at least one location parameter and at least one descriptive parameter;
based on the first set of parameters and the second set of parameters, calculating a quantitative measure of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest;
in response to the quantitative proximity indicator exceeding the proximity threshold, creating a complex point of interest representing the first point of interest and the second point of interest, and creating a complex point of interest includes the following steps:
applying a heuristic algorithm to the first point of interest and the second point of interest to determine one of these points of interest as the main point of interest and to determine the other point of interest as a secondary point of interest;
receiving, from the storage device, an information card of the main point of interest;
Assignment, to a complex point of interest, at least partially, of information from the information card of the main point of interest. 2. The method according to p. 1, further comprising:
receiving, from a storage device, a card of a secondary point of interest;
assignment, to a complex point of interest, at least a portion of at least one parameter from the card of a secondary point of interest. 3. The method according to any one of paragraphs. 1-2, in which the server generates many cards of points of interest, and one card of a point of interest corresponds to one object. 4. The method according to claim 3, wherein generating a plurality of cards of points of interest includes receiving by the server information about objects that could potentially be represented by points of interest, including obtaining a predetermined set of parameters for each object from a plurality of objects, the predetermined set of parameters including at least one location parameter and at least one descriptive parameter, and assigning corresponding parameters to the corresponding point of interest cards. 5. The method according to claim 4, in which information about objects that can potentially be represented by points of interest is obtained from open data sources. 6. The method according to claim 1, in which obtaining information about objects that could potentially be represented by points of interest, further includes assessing the priority of the data sources, and obtaining at least part of the set of parameters of the corresponding potential point of interest from the data source that has the highest priority compared to other data sources. 7. The method according to p. 1, in which the descriptive parameter is any of: the name of the object, the description of the object, a photograph of the object, contact details, a hyperlink to the site. 8. The method of claim 1, wherein the predefined set of parameters further includes an object significance parameter and in which the heuristic algorithm for determining the main point of interest and the secondary point of interest takes into account the object significance parameter. 9. The method of claim 8, wherein the significance parameter of the object is determined by determining its photorating. 10. The method of claim 1, wherein the set of word significance markers is pre-programmed, and in which the heuristic algorithm for determining the main point of interest and the secondary point of interest takes into account word importance markers from the set of word significance markers. 11. The method according to p. 1, further comprising receiving a user’s request to provide him with information about any of: the first object and the second object and, in response to receiving this request, providing the user with information from the card of a complex point of interest. 12. The method according to claim 1, wherein the location parameter is determined taking into account a subparameter of geographical proximity and a subparameter of the density of objects, the subparameter of geographical proximity depends on the distance between the objects, and the subparameter of the density of objects depends on the number of objects per unit area. 13. A computer including a processor, where the configuration of the processor is configured so that the computer can perform:
obtaining a card of a first point of interest and a card of a second point of interest from a plurality of cards of points of interest, each of the cards of points of interest includes a predetermined set of parameters describing a corresponding object represented by a corresponding point of interest;
obtaining a first plurality of parameters from a first card of a first point of interest, a first plurality of parameters including at least one location parameter and at least one descriptive parameter;
obtaining a second plurality of parameters from a second card of a second point of interest, a second plurality of parameters including at least one location parameter and at least one descriptive parameter;
based on the first set of parameters and the second set of parameters, calculating a quantitative measure of the proximity of the first point of interest and the second point of interest, indicating the potential for associating the first point of interest and the second point of interest;
in response to the quantitative proximity indicator exceeding the proximity threshold, creating a complex point of interest representing the first point of interest and the second point of interest, and creating a complex point of interest includes the following steps:
applying a heuristic algorithm to the first point of interest and the second point of interest to determine one of these points of interest as the main point of interest and to determine another point of interest as a secondary point of interest,
receiving, from the storage device, an information card of the main point of interest;
Assignment, to a complex point of interest, at least partially, of information from the information card of the main point of interest. 14. The computer according to claim 13, where the processor configuration is configured so that the computer can additionally perform:
receiving, from a storage device, a card of a secondary point of interest;
assignment, to a complex point of interest, at least a portion of at least one parameter from the card of a secondary point of interest. 15. The computer according to claim 13, in which the processor configuration is configured so that the computer can generate many cards of points of interest, and one card of a point of interest corresponds to one object. 16. The computer of claim 15, wherein generating a plurality of point of interest cards includes receiving a computer with information about objects that could potentially be represented by points of interest, including obtaining a predetermined set of parameters for each object from a plurality of objects, wherein the predetermined set of parameters includes at least one location parameter and at least one descriptive parameter, and assigning corresponding parameters to the corresponding point of interest cards. 17. The computer according to claim 16, in which information about objects that can potentially be represented by points of interest is obtained from open data sources. 18. The computer according to claim 13, in which obtaining information about objects that could potentially be represented by points of interest, further includes assessing the priority of the data sources and obtaining at least part of the set of parameters of the corresponding potential point of interest from the data source that has the highest priority for compared to other data sources. 19. The computer according to claim 13, in which the descriptive parameter is any of: the name of the object, the description of the object, a photograph of the object, contact information, a hyperlink to the site. 20. The computer according to claim 13, in which the predefined set of parameters further includes an object significance parameter, and in which the heuristic algorithm for determining the main point of interest and secondary interest point takes into account the object significance parameter. 21. The computer according to claim 20, in which the parameter of the significance of the object is determined by determining its photorating. 22. The computer of claim 13, wherein the set of word significance markers is pre-programmed, and in which the heuristic algorithm for determining a primary point of interest and a secondary point of interest takes into account word importance markers from a set of word significance markers. 23. The computer according to claim 13, in which the configuration of the processor is configured so that the computer can additionally receive a user request to provide him with information about any of: the first object and the second object and, in response to receiving this request, providing the user with information from the card integrated point of interest. 24. The computer according to claim 13, in which the location parameter is determined taking into account a subparameter of geographical proximity and a subparameter of density of objects, the subparameter of geographical proximity depends on the distance between the objects, and the subparameter of the density of objects depends on the number of objects per unit area

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