NL2032064B1 - Multi-round searching and cataloging of search results - Google Patents
Multi-round searching and cataloging of search results Download PDFInfo
- Publication number
- NL2032064B1 NL2032064B1 NL2032064A NL2032064A NL2032064B1 NL 2032064 B1 NL2032064 B1 NL 2032064B1 NL 2032064 A NL2032064 A NL 2032064A NL 2032064 A NL2032064 A NL 2032064A NL 2032064 B1 NL2032064 B1 NL 2032064B1
- Authority
- NL
- Netherlands
- Prior art keywords
- search
- result
- results
- query
- criteria elements
- Prior art date
Links
- 238000000034 method Methods 0.000 claims description 65
- 230000004044 response Effects 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 3
- 238000013500 data storage Methods 0.000 claims description 3
- 201000010099 disease Diseases 0.000 claims 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims 1
- 238000004891 communication Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 9
- 230000000977 initiatory effect Effects 0.000 description 7
- 230000003993 interaction Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000000717 retained effect Effects 0.000 description 4
- 238000013459 approach Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 101000822695 Clostridium perfringens (strain 13 / Type A) Small, acid-soluble spore protein C1 Proteins 0.000 description 1
- 101000655262 Clostridium perfringens (strain 13 / Type A) Small, acid-soluble spore protein C2 Proteins 0.000 description 1
- 101000655256 Paraclostridium bifermentans Small, acid-soluble spore protein alpha Proteins 0.000 description 1
- 101000655264 Paraclostridium bifermentans Small, acid-soluble spore protein beta Proteins 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000007177 brain activity Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 238000013515 script Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000026683 transduction Effects 0.000 description 1
- 238000010361 transduction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3325—Reformulation based on results of preceding query
- G06F16/3326—Reformulation based on results of preceding query using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages
- G06F16/3328—Reformulation based on results of preceding query using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages using graphical result space presentation or visualisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9532—Query formulation
Abstract
A computing system facilitates multi-round searching. The computing system generates first results data based on a first search query. The first results data includes a first set of search results in which each search result of one or more search results of the first set identifies: a 5 respective content item, search criteria elements of the first search query satisfied by the content item, and suggested search criteria elements extracted from the content item that are semantically linked to search criteria elements of the first search query. The computing system generates second results data that includes a second set of search results based on a second search query. The second search query includes at least some of the first set of search criteria 10 elements of the first search query and at least one of: the search criteria elements or suggested search criteria elements identified by a user-selected, target search query.
Description
MULTI-ROUND SEARCHING AND CATALOGING OF SEARCH RESULTS
[0001] Computer-implemented search engines have been developed that provide search results responsive to user-initiated search queries. Search queries may target specific forms of data, including Internet or other network resources, file directories, databases, or other collections of data. Search queries may be constructed from one or more search criteria elements, including text-based search terms using natural language and predefined filter criteria that are user selectable.
[0002] According to an example of the present disclosure, a computing system facilitates multi-round searching of search results. The computing system receives a first search query that includes a first set of one or more search criteria elements (e.g., search terms), and generates first results data based on the first search query.
[0003] As an example, the first results data includes a first set of search results in which each search result of one or more search results of the first set of search results identifies: a respective content item, one or more search criteria elements of the first search query satisfied by the content item, and one or more suggested search criteria elements extracted from the content item that are semantically linked to the first set of one or more search criteria elements.
[0004] The computing system receives a command to catalog a target search result of the first set of search results, and adds the target search result to a session-specific catalog of search results responsive to the command.
[0005] The computing system generates second results data including a second set of search results based on a second search query that includes at least some of the search criteria elements of the first search query and at least one of: the one or more search criteria elements identified by the target search result and/or the one or more suggested search criteria elements identified by the target search result. The second set of search results include the target search result and one or more additional search results.
[0006] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.
S [0007] FIG. 1 is a schematic diagram depicting an example computing environment that includes a computing system.
[0008] FIG. 2A is a schematic diagram depicting example user interfaces of FIG. 1.
[0009] FIG. 2B is a schematic diagram depicting the search interface of FIG. 2A following a revised search.
[0010] FIG. 3 depicts an example search interface populated with example data.
[0011] FIGS. 4A-4E is a flow diagram depicting an example search method, including a method component to facilitate multi-round searching.
[0012] FIG. 5 is a schematic diagram of an example computing system.
[0013] Search tasks may be more difficult for users that are relatively inexperienced with a particular search domain. For example, users may be unfamiliar with terminology used within a particular domain of information or may be unaware of underlying concepts of that domain. Thus, users may be inefficient at constructing searches to be performed by a computing system.
[0014] One approach that has the potential to address the above issues, as described herein, includes providing users with suggested search criteria elements (e.g., suggested search terms) that enable users to conduct revised searches over one or more follow-on rounds of searching. In at least some examples, suggested search criteria elements may be extracted from content items that are identified at each round of searching. Suggested search criteria elements may be presented to users via a search interface to enable users to modify search queries for follow-on searching.
[0015] Follow-on search queries may be programmatically or manually constructed to include search criteria elements satisfied by content items of target search results selected by a user. For example, revised search queries may be constructed that are responsive to user interests, as expressed by user selection of target search results. Additionally or alternatively, follow-on search queries may be programmatically or manually constructed to include suggested search criteria elements extracted from content items of target search results that are selected by a user. These suggested search criteria elements may be provided as feedback to users to enhance search efficiency by enabling users to review and select target suggested search criteria elements of interest for further search refinement and exploration.
[0016] As users revise a search over one or more follow-on rounds of searching, target search results of interest to the user may be selectively added to a session-specific catalog of search results, enabling the user to build a collection of search results over any suitable number of rounds of searching. Features of cataloged search results may be used to further revise search criteria over one or more rounds of searching. The session-specific catalog of search results may be selectively shared by the user with other users. Additionally, the session-specific catalog of search results may be stored in association with user accounts, enabling users to access and continue particular search sessions at a later time. As an example, a user may initiate a search session in which the user performs one or more rounds of searching on a topic to create a session-specific catalog that contains one or more search results. Later, the user may access and modify the session-specific catalog, for example, by adding additional search results to the session-specific catalog by conducting one or more additional rounds of searching for that search session. Thus, a search session may span any amount of time and number of rounds of searching, and the session-specific catalog may contain search results obtained from any of those rounds of searching. These aspects of the present disclosure may enable complex searching tasks to be performed in a collaborative manner and over a period of time, while also preserving past work product of users.
[0017] In at least some examples, identification of search results and/or extraction of suggested search criteria elements may be performed using computer-implemented natural language services and/or a predefined schema that semantically links entities with properties of those entities. As users conduct searches, the schema used to extract suggested search criteria elements may be grown or otherwise modified at the search service to incorporate new relationships between entities and properties for the benefit of other users.
[0018] FIG. 1 is a schematic diagram depicting an example computing environment 100. In this example, a computing system 110 of computing environment 100 includes a search service 112 that may be accessible to client devices over a communications network 120, such as the Internet. An example client device 130 having an application program 132 for accessing search service 112 is depicted in FIG. I.
[0019] Applicant program 132 may present one or more user interfaces 134 by which a user can interact with application program 132 and search service 112. User interfaces 134 may form part of application program 132 or may form part of search service 112, depending on implementation. As an example, a user may provide a search query to application program
132 via user interfaces 134, which may be processed by search service 112 or by search service 112 in combination with application program 132 to present one or more search results responsive to the search query via the one or more user interfaces.
[0020] In at least some examples, application program 132 may take the form of a special-purpose application program that is specifically configured to interact with search service 112. In this example, user interfaces 134 may form part of application program 132. In other examples, application program 132 may take the form of a general-purpose browser program by which search service 112 may be accessed. In this example, user interfaces 134 may form part of search service 112, and application program 132 may provide access to (e.g, render) user interfaces 134 of search service 112.
[0021] Search results generated by search service 112, based on search terms of a search query, may be identified or otherwise selected from a collection of content items 140, an example of which is content item 142. The collection of content items 140 may take the form of web resources (e.g., webpages or other resources of websites) accessible via communications network 120, as an example. In this example, websites may be hosted at third- party computing devices and/or at computing system 110. Additionally, or alternatively, content items 140 may include other forms of content or data, such as e-books, music, movies, text documents, spreadsheets, presentations, file directories, databases, etc. that are hosted at third-party computing devices, at computing system 110, and/or at client devices (e.g., at client device 130 as local content items stored at the client device).
[0022] Computing system 110, in at least some examples, may take the form of one or more server computing devices that interact with client computing devices (e.g., client device 130) via communications network 120. While client device 130 is depicted as a separate component from computing system 110, in at least some examples, computing system 110 and client device 130 may take the form of an individual computing device such that application program 132 and search service 112 are executed on the same device. As an example, a computing device may execute both application program 132 and search service 112, in which case application program 132 and search service 112 may form part of the same program.
[0023] In at least some examples, search service 112 may be operable to generate search results based on search queries using a schema 114. Schema 114 may define semantic links between entities and properties of those entities. Search criteria elements of a search query may take the form of entities, properties (e.g., describing attributes of the entities), or locations (e.g., a physical location of the entities). Suggested search criteria elements may take the form of entities or properties semantically linked to the search criteria elements within schema 114, as an example.
[0024] As an example, a search criteria element (e.g., the term “HIKE”) may be defined as an entity within schema 114, and one or more suggested search criteria elements (e.g., 5 “WATERFALLS”, “STROLLER”, “RESTROOM”, “FRIENDLY”, etc.) may be defined as properties of the entity within the schema. As another example, a search criteria element (e.g., “WATERFALLS”) may be defined as a property of an entity within the schema and a suggested search criteria element (e.g., “HIKES”) may be defined as the entity within the schema. By providing users with suggested search criteria elements in response to an initial search query, subsequent search queries may be performed by the user that include suggested search criteria element that would not have otherwise been known or considered by the user.
[0025] Schema 114 may be programmatically updated over time to include new or modified semantic links between entities and properties responsive to user interaction with search service 112. Alternatively or additionally, schema 114 may be manually updated over time by operators (e.g., as curators) of search service 112 to include new or modified semantic links between entities and properties. As an example, search criteria may be captured per entity for potential inclusion in the schemas as properties of the entity. Curation of the schema may be based on feedback users as they interact with the search service, including users adding search results to catalogs, users sharing search results, or users selecting suggested search criteria elements for revised searches. Curation of the schema may be based on input from human trainers, frequency of occurrence of terms in natural language, frequency of occurrence on entities, and inferences from natural language models (e.g., of services 150 described below) or other models.
[0026] In at least some examples, search service 112 may be operable to generate search results based on search queries using natural language services 150. Natural language services 150 may implement one or more natural language models. For example, natural language services 150 may implement one or more autoregressive language models that use machine learning (e.g., deep learning) to produce human-like text based on a given input.
Search service 112 may provide some or all of the search terms of a search query to natural language services 150, which may return one or more additional search terms. As examples, these additional search terms may be used to identify content items that satisfy a search query or may be used as suggested search criteria elements. In each of these examples, natural language services 150 may be used by search service 112 to enhance search results by inferring user intent from natural language contained in the search query. Natural language services 150 may support one or more application programming interfaces (APIs) by which search terms are provided to or received from service 150. Natural language services 150 may reside at third- party computing devices, computing system 110, or at client devices, as examples.
[0027] FIG. 2A is a schematic diagram depicting example user interfaces 134 of FIG. 1, including a search interface 210 by which search queries may be constructed and initiated, and search results may be presented; a catalog interface 212 within which search results selected by a user may be cataloged; and a share interface 214 by which search results may be shared with other users.
[0028] Search interface 210 may include a search field 220 by which a user may input and initiate a search query of one or more search terms. A search query that is input and initiated via search field 220 may be processed by search service 112, and a plurality of search results 222-1, 222-2, 222-N generated by the search service for the search query may be presented via search interface 210. The term “N” in this example refers to any suitable quantity of search results, and may refer to a predetermined quantity that is defined by application program 132 or search service 112.
[0029] Search interface 210 may further include a set of primary navigation selectors 224, which may include: an account navigation selector 226 that, upon selection by a user, navigates user interface 134 to an account interface; a catalog navigation selector 228 that, upon selection by a user, navigates user interface 134 to catalog interface 212; and a share navigation selector 230 that, upon selection by a user, navigates user interface 134 to share interface 214.
[0030] Each search result in the example of FIG. 2A includes or is otherwise associated with a variety of search result information and user tools (denoted by a suffix 1, 2, through N of each search result), including: a content location identifier 240 that identifies a network or file location of a content item of the search result (e.g., a URL, URL file path within a file directory, etc.); a cataloging selector 242 that, upon selection by a user, catalogs the search result by adding the search result to a session-specific catalog; a content identifier 244 that identifies the content item (e.g., a title of the content item); a set of one or more satisfied search criteria elements 246 that identify search terms of the search query that are satisfied by the content item; a set of one or more non-satisfied search criteria elements 248 that identify search terms of the search query that are not satisfied by the content item; and a set of one or more suggested search criteria elements 250 that identify suggested search terms that are extracted from the content item.
[0031] Suggested search criteria elements 250 may include suggested search terms, as suggestions to the user, which can be used to revise or otherwise augment the previous search query. In at least some examples, suggested search criteria elements 250 may include or be associated with respective element selectors 252 of search interface 210. Upon selection of a particular element selector by a user, a revised search query may be initiated by the search service using the suggested search criteria element (e.g, a suggested search term) corresponding to the selected element selector. Presentation of suggested search criteria elements may serve as suggestions for additional search queries that can be selectively initiated by a user through selection of a corresponding element selector. Responsive to selection of a particular element selector, the search service may generate one or more additional search results using at least the corresponding suggested search criteria element, in combination with the previous search criteria elements (e.g., the previous search terms) of the previous search query, which may replace or augment the previous search results within search interface 210.
Thus, a user may obtain additional or revised search results within search interface 210 by selecting particular selectors associated with suggested search criteria elements.
[0032] As an example, referring also to FIG. 2B, upon selection of a particular element selector of element selectors 252-1 within search result 222-1, additional search results 222- 2.1 through 222-N.1 may be presented within search interface 210 that replace previous search results 222-2 through 222-N of FIG. 2A. Within FIG. 2B, features of additional search results 222-2.1 through 222-2.N are again denoted by a corresponding suffix 2.1 through 2.N.
[0033] In this example, search result 222-1 has been retained in search interface 210, at least because an element selector that was selected by the user corresponds to a suggested search criteria element that has been extracted from the content item of search result 222-1. By contrast, the content items of previous search results 222-2 through 222-N of FIG. 2A that were replaced in FIG. 2B do not satisfy the suggested search criteria element. Additionally, within
FIG. 2B, primary navigation selectors 224 may persist within search interface 210 across a plurality of search queries to provide the user within the ability to navigate to other interfaces.
[0034] Upon selection by a user of catalog selector 242 associated with a particular search result, the search result may be added to a session-specific catalog of search results for the search session. Each search session may span one or more search queries, including an initial search query (e.g., via search interface 210 of FIG. 2A) and one or more revised search queries (e.g., via search interface 210 of FIG. 2B). Catalog interface 212, for example, may include one or more catalogs 260-1, 260-2, 260-Z, where the quantity term “Z” represents a quantity of catalogs generated by the user for respective search sessions.
[0035] Example catalog 260-1, for example, refers to a session-specific catalog for a search session that includes one or more search queries (e.g., an initial search query and one or more revised search queries via search interface 210 of FIGS. 2A and 2B). In this example, cataloging selector 242-1 of search result 222-1 has been selected by a user, resulting in search result 222-1 being added to catalog 260-1 for the search session. A catalog may include any suitable quantity of search queries added by the user to the catalog, as denoted by the term “X” in FIG. 2A.
[0036] In at least some examples, adding a search result to a catalog may cause that search result being retained within search interface 210 over any number of revised searches for that search session. For example, search result 222-2 may be retained in search interface 210 of FIG. 2B if search result 222-2 was added to catalog 260-1 for the search session.
[0037] As previously described, catalog navigation selector 228 may be used to navigate from search interface 210 to catalog interface 212. Within catalog interface 212, each catalog may include or be associated with a continue session selector 270 (denoted by a suffix 1, 2, Z that corresponds to the catalog suffix) that enables a user to return to a search session of the catalog. For example, catalog 260-1 includes a continue session selector 270-1 that, upon selection by a user, navigates user interface 134 to search interface 210 within which cataloged search results may be presented along with other search results generated for a current search query of the search session. A user may navigate to other search sessions by selecting continue session selector 270 associated with a particular catalog. For example, a user may discontinue or pause the search session associated with catalog 260-1, and continue the search session associated with catalog 260-2 by selecting continue session selector 270-2.
[0038] Share interface 214 may be accessed via share navigation selector 230 from search interface 210 within a given search session to share the current search results presented in search interface 210, or via share selectors 272-1, 272-2, through 272-Z associated with respective catalogs 260-1, 260-2, through 260-Z to share particular catalogs of search results.
For example, a user selection of share selector 272-1 may be used to share the search results of catalog 260-1, which includes at least cataloged search result 222-1. As another example, a user selection of share navigation selector 230 within FIG. 2A may be used to share search results 222-1, 222-2 through 222-N of search interface 210 of FIG. 2A. As yet another example, a user selection of share navigation selector 230 within FIG. 2B may be used to share search results 222-1, 222-2.1 through 222-N.1 of search interface 210 of FIG. 2B.
[0039] Share interface 214 may include a share target field 280 to which user identifiers or other address identifiers may be input to identify users or user accounts to which the search results are to be shared. Such identifiers may take the form of an email address, a phone number, a contact name within a contact directory, a user account name, etc. Search interface 214 may include a share initiate selector 282 to initiate sharing of the search results with the user or address identified in field 280.
[0040] FIG. 3 depicts an example search interface 310. Search interface 310 is an example of search interface 210 of FIGS. 2A and 2B. In this example, a search query input to search field 312 includes a first set of search criteria elements in the form of the search terms: “SUMMER CAMPS FOR A 15 Y/O NEAR SEATTLE 2022”. A variety of search results 314- 1,314-2, 314-3, 314-4, etc. are presented based on and responsive to the search query. FIG. 3 additionally depicts examples of an account navigation selector at 330, a catalog navigation selector at 332, and a share navigation selector at 334, as examples of selectors 226, 228, and 230 respectively.
[0041] As described with reference to search result 314-2, each search result of example search interface 310 includes a content location identifier (e.g., 316), a cataloging selector (e.g., 318), a content identifier (e.g., 320), satisfied search criteria elements (e.g., 322), non-satisfied search criteria elements (e.g., 324) (if any), and element selectors (e.g., 326) associated with suggested search criteria elements (e.g., “GUIDE”, “FREQUENTLY ASKED
QUESTIONS”, “GENERAL INFORMATION”).
[0042] In at least some examples, upon a user selecting a target search result, either by selecting the cataloging selector of that search result or by selecting an element selector associated with suggested search criteria elements of that search result, the search query within search field 312 may be programmatically updated to include features of the target search result. As an example, by selecting cataloging selector 318 of search result 314-2 as a target search result, search field 312 may be programmatically updated to include some or all of the suggested search criteria elements of search result 314-2. Additionally or alternatively, satisfied search criteria elements (e.g., 322) may be programmatically retained in search field 312 and/or non-satisfied search criteria elements (e.g., 324) may be programmatically removed from search field 312. As another example, a user may select a target suggested search criteria element (e.g., for “GUIDE”) as a command to programmatically add that element to search field 312. Furthermore, in at least some examples, a subsequent search query may be programmatically initiated using the updated search query responsive to a user selecting a target search result or a target suggested search criteria element. In other examples, follow-on searches using programmatically updated search fields may be manually initiated by a user (e.g., by selecting a “submit” selector).
[0043] FIGS. 4A — 4E are flow diagrams depicting an example searching method 400.
Method 400 may be performed by a computing system of one or more computing devices. As an example, method 400 may be performed by computing system 110 of FIG. | executing search service 112. In at least some examples, aspects of method 400 may be performed at a client device (e.g., client device 130) that is remotely located from computing system 110 or forms part of computing system 110.
[0044] At 410, the method includes initiating a new search session. As an example, a user may launch an application program (e.g., 132 of FIG. 1) to access a search interface (e.g, 210 of FIG. 2A) of a search service (e.g., 112 of FIG. 1).
[0045] At 412, the method includes receiving a first search query that includes a first set of one or more search criteria elements. As an example, a user may provide the first search query via search field 220 of FIG. 2A, which is received by search service 112 of FIG. 1.
[0046] At 414, the method includes generating first results data based on the first search query. As an example, search service 112 of FIG. 1 generates first results data based on the one or more search criteria elements received at 412.
[0047] At 416, the method includes presenting the first results data via a user interface.
As an example, search service 112 may output the first results data for presentation at search interface 210.
[0048] As indicated at 420, the first results data includes a first set of search results (e.g. a plurality of search results, represented by the term “N” in FIG. 2A). As an example, the first set of search results may include a plurality of search results. One or more search results (some or all) of the first set of search results may each identify a respective content item, as indicated at 422. As part of generating the first results data at 420, the method further includes, for each search result of one or more search result (some or all) of the first set of search results identifying, at 424, the content item for each search result of the one or more search results (some or all) of first set of search results. As an example, search service 112 of FIG. 1 may identify content items (e.g., among content items 140 of FIG. 1) that satisfy one or more of the first set of search criteria elements received at 412.
[0049] Each search result of the one or more search results (some or all) of the first set of search results may further identify one or more search criteria elements of the first search query that are satisfied by the content item, as indicated at 426. As part of generating the first results data at 420, the method further includes, for each search result of the one or more search results (some or all) of the first set of search results, identifying the one or more search criteria elements of the first search query that are satisfied by the content item at 428.
[0050] Each search result of the one or more search results (some or all) of the first set of search results may further identify one or more suggested search criteria elements, as indicated at 430. As an example, the one or more suggested search criteria elements may be extracted from the content item that are semantically linked to the first set of one or more search criteria elements. As part of generating the first results data at 420, the method further includes, for each search result of the one or more search results (some or all) of the first set of search results identifying, at 432, the one or more suggested search criteria elements by extracting the one or more suggested search criteria elements from the content item based on a schema (e.g., 114 of FIG. 1) and/or using a natural language service (e.g., 150 of FIG. 1).
[0051] In at least some examples, for each search result of the one or more search results (some or all0 of the set of search results, extracting each suggested search criteria element from the content item may be performed by identifying a semantic link between a search criteria element of the first search query that is satisfied by the content item and the suggested search criteria element. As a first example, the semantic link is defined by a schema (eg. 114 of FIG. 1), the search criteria element is defined as an entity within the schema, and the suggested search criteria element is defined as a property of the entity within the schema.
As a second example, the semantic link is defined by a schema (e.g., 114 of FIG. 1), the search criteria element is defined as a property of an entity within the schema, and the suggested search criteria element is defined as the entity within the schema.
[0052] In at least some examples, generating search results may include, providing each search criteria element of the search query to a natural language service (e.g., 150 of FIG. 1), receiving a suggested search criteria element for the search criteria element from the natural language service, and identifying the content item for the search results data based, at least in part, on the suggested search criteria element being satisfied by the content item.
[0053] Each search result of the one or more search results (some or all) of the first set of search results may further identify one or more search criteria elements of the first search query that are not satisfied by the content item (if any), as indicated at 434. As part of generating the first results data at 420, the method further includes, for each search result of the one or more search results (some or all) of the first set of search results identifying, at 436, the one or more search criteria elements of the first search query that are not satisfied by the content item (if any).
[0054] The first results data presented at 416 may include the respective content 1tem, the one or more search criteria elements satisfied by the content item, the one or more suggested search criteria elements extracted from the content item, and the one or more search criteria elements not satisfied by the content item (if any). From presentation of the first results data at 416, the method may proceed to one or more of: cataloging of search results as indicated at 438 (see e.g., FIG. 4B), sharing of current results data (e.g., first results data) as indicated at 440 (see e.g., FIG. 4C), or initiating a revised search as indicated at 442 (see e.g., FIG. 4D).
[0055] Referring to FIG. 4B, as part of cataloging of search results as previously described at 438, the method at 450 includes receiving a command to catalog a target search result of the first set of search results. As an example, a user may select a cataloging selector (e.g, 242-1 of FIG. 2A) associated with a target search result (e.g., 222-1 of FIG. 2A) to provide the command to catalog the target search result. At 452, the method includes adding the target search result to a session-specific catalog of search results (for the session initiated at 410) responsive to the command received at 450. As an example, target search result (e.g., 222-1 of FIG. 2A) may be added to session-specific catalog 260-1 of FIG. 2A. Operations 450 and 452 may be repeated, as indicated at 454, to enable a user to add additional target search results to the session-specific catalog.
[0056] In at least some examples, user selection of target search results for cataloging may be used as feedback to the search service to update the schema (e.g., schema 114). As an example, user selection of target search results may indicate that suggested search criteria elements associated with those target search results represent accurate semantic links between entities and properties.
[0057] From operation 452, the method may proceed to one or more of: sharing the session-specific catalog as indicated at 444 (e.g., see FIG. 4E), sharing of current results data (e.g., first results data or subsequent results data from a revised search) as indicated at 440 (e.g., see FIG. 4C), or initiating a revised search as indicated at 442 (e.g., see FIG. 4D). In at least some examples, the method may programmatically proceed to a revised search as indicated at 442 responsive to a target search result being added to a session-specific catalog at 452 and/or responsive to the command received at operation 450.
[0058] Referring to FIG. 4C, as part of sharing current results data as previously described at 440, the method at 456 includes receiving a command to share the current results data of a search interface. As an example, a user may select a share navigation selector (e.g., 230 of FIG. 2A) to provide the command to share the current results data (e.g., search results 222-1, 222-2 through 222-N) of search interface 210. As part of operation 456, the method may include receiving input of one or more share targets at 458. As an example, a user may provide the one or more share targets via a share target field (e.g., 280 of FIG. 2A). At 460, the method includes providing the current results data to the one or more share targets. As an example, a user may initiate sharing of the current search results by selecting selector 282 of FIG. 2A.
[0059] In at least some examples, sharing of current search results by users may be used as feedback to the search service to update the schema (e.g., schema 114). As an example, sharing of current search results by users may indicate that suggested search criteria elements associated with those search results represent accurate semantic links between entities and properties within the schema.
[0060] From operation 460, the method may proceed to one or more of: cataloging of search results as indicated at 438 (e.g., see FIG. 4B) or initiating a revised search as indicated at442 (e.g. see FIG. 4D).
[0061] Referring to FIG. 4D, as part of initiating a revised search as previously described at 442, the method at 462 includes receiving a command to initiate a revised search for second (or subsequent) results data. The command to initiate the revised search may be provided in a variety of ways.
[0062] As a first example, the revised search may be initiated programmatically responsive to a target search result being added to a session-specific catalog (as the commend received at 462), such as previously described with reference to FIG. 4B. In this example, revised search results may be based, at least in part, on features of the target search result. Such features may include search criteria elements satisfied by the content item of the target search result, including search criteria elements of the first (or previous) search query. As another example, suggested search criteria elements of the target search result that were extracted from the content item may be included in the second search query, to augment the search criteria elements of the first (or previous) search query. As yet another example, search criteria elements of the first (previous) search query that were not satisfied by the content item of the target search result may be excluded from the second search query. In at least some examples, the search field of the search interface may be programmatically updated to reflect a second (or subsequent) set of search criteria elements for the second (or subsequent) search query, based on user interaction with one or more target search results from the first (or previous) search results.
[0063] As a second example, the revised search may be initiated by a user selecting an element selector associated with a suggested search criteria element of a target search result.
As an example, a user may select “STEM” as a target suggested search criteria element within the search interface of FIG. 3 to include the search term “STEM” within a revised search query in combination with some or all of the search criteria elements of the first (or previous) search query. In this example, the revised search results may be based, at least in part, on the target suggested search criteria element selected by the user. In at least some examples, the search field of the search interface may be programmatically updated to reflect a second (or subsequent) set of search criteria elements for the second (or subsequent) search query, based on user interaction with one or more target search results from the first (or previous) search results.
[0064] As a third example, the revised search may be initiated by a user manually modifying the search query within search field 220 and/or by the user submitting the modified search query by selecting a submit selector of the search interface. In this example, revised search results may be based, at least in part, on the modified search query. In examples such as this where a user manually modifies the search query, this modification may be based on the user’s observation of suggested search criteria elements and/or search criteria elements from the previous search query that are identified as being satisfied or not satisfied by current search results.
[0065] At 464, the method includes generating second (or subsequent) results data including a second (or subsequent) set of search results based on a second search query. The second search query includes a second set of one or more search criteria elements. The second set of search criteria elements of the second search query may include one or more (e.g., some or all) of the first set of search criteria elements of the first search query. The second set of search criteria elements of the second search query may further include at least one of: (1) the one or more search criteria elements identified as being satisfied by the target search result, (2) the one or more suggested search criteria elements identified by the target search result. In at least some examples, the second results data is generated based on both: the one or more search criteria elements identified by the target search result, and the one or more suggested search criteria elements identified by the target search result. As indicated at 466, the second set of search results may include the target search result and one or more additional search results.
[0066] As previously described with reference to the first set of search results, each search result of one or more search results (some or all) of the second (or subsequent) set of search results identifies: a respective content item as indicated at 468; one or more search criteria elements of the second search query that are satisfied by the content item as indicated at 472; one or more suggested search criteria elements extracted from the content item that are semantically linked to the second set of one or more search criteria elements as indicated 476; and one or more search criteria elements of the second search query that are not satisfied by the content item (if any) as indicated at 480.
[0067] As previously described with reference to generating first results data of FIG. 4A, generating the second results data may include, for each search result of the one or more search results (some or all) of the second set of search results: identifying the content item of that search result at 470; identifying the one or more search criteria elements satisfied by the content item of the search result at 474; identifying the one or more suggested search criteria elements extracted from the content item of the search result that are semantically linked to the second set of one or more search criteria elements at 478; and identifying the one or more search criteria elements of the second search query that are not satisfied by the content item at 482.
[0068] In at least some examples, for each search result of one or more search results (some or all) of the set of search results, extracting each suggested search criteria element from the content item may be performed by identifying a semantic link between a search criteria element of the first search query that is satisfied by the content item and the suggested search criteria element. As a first example, the semantic link is defined by a schema (e.g., 114 of FIG. 1), the search criteria element is defined as an entity within the schema, and the suggested search criteria element is defined as a property of the entity within the schema. As a second example, the semantic link is defined by a schema (e.g., 114 of FIG. 1), the search criteria element is defined as a property of an entity within the schema, and the suggested search criteria element is defined as the entity within the schema.
[0069] At 484, the method includes presenting the second results data via a user interface. As an example, the second results data may be presented via search interface 210, as previously described with reference to FIG. 2B.
[0070] Following presentation of second (or subsequent) results data at 484, the method may proceed to one or more of cataloging as indicated at 438 (e.g., see FIG. 4B), sharing of current results data as indicated at 440 (e.g., see FIG. 4C), initiating a revised search as indicated at 442 (e.g., repeat the flow diagram of FIG. 4D).
[0071] Referring to FIG. 4E, sharing of a session-specific catalog may be performed following cataloging of one or more target search results, as previously described with reference to FIG. 4B. At 486, the method includes receiving a command to share a session- specific catalog of search results. As previously described with reference to FIG. 2A, a share selector (e.g., 272) associated with each catalog (e.g., 260) may be selected by a user as at least part of the command to share the catalog. As part of the command to share the catalog, the method at 488 may include receiving an input of one or more share targets to which the catalog is to be shared and/or user selection of a share initiate selector (e.g., 282). As an example, a share target field (e.g., 280) of a share interface (e.g., 214) may be used to enable a user to specify one or more share targets. At 490, the method includes providing the catalog of search results to the one or more share targets responsive to the command received at 486.
[0072] In at least some examples, sharing of session-specific catalogs by users may be used as feedback to the search service to update the schema (e.g, schema 114). As an example, sharing of catalogs by users may indicate that suggested search criteria elements associated with those cataloged search results represent accurate semantic links between entities and properties within the schema.
[0073] From operation 490, the method may proceed to one or more of: cataloging of search results as indicated at 438 (e.g., see FIG. 4B), sharing of current results data as indicated at 440 (e.g., see FIG. 4C), or initiating a revised search as indicated at 442 (e.g., see FIG. 4D).
[0074] As previously described, the methods and processes described herein may be tied to a computing system of one or more computing devices. In particular, such methods and processes may be implemented as a computer-application program or service, an application- programming interface (API), a library, and/or other computer-program product.
[0075] FIG. 5 schematically shows an example of a computing system 500 that can perform one or more of the methods and processes described herein. Computing system 500 is shown in simplified form. Computing system 500 may take the form of one or more personal computers, server computers, tablet computers, home-entertainment computers, network computing devices, gaming devices, mobile computing devices, mobile communication devices (e.g., a smart phone), and/or other computing devices.
[0076] Computing system 110 of FIG. 1 1s an example of computing system 500. Client device 130 of FIG. 1 is another example of computing system 500. Computing system 110 in combination with client device 130 of FIG. 1 is yet another example of computing system 500.
[0077] Computing system 500 includes a logic machine 510, a data storage machine 512, and an input / output subsystem 514. Computing system 500 may include a display subsystem, a user input subsystem, and communication subsystem, as components of input / output subsystem 514.
[0078] Logic machine 510 includes one or more physical devices configured to execute instructions. For example, the logic machine may be configured to execute instructions that are part of one or more applications, services, programs, routines, libraries, objects, components, data structures, or other logical constructs. Such instructions may be implemented to perform a task, implement a data type, transform the state of one or more components, achieve a technical effect, or otherwise arrive at a desired result.
[0079] The logic machine may include one or more processors configured to execute software instructions. Additionally or alternatively, the logic machine may include one or more hardware or firmware logic machines configured to execute hardware or firmware instructions.
Processors of the logic machine may be single-core or multi-core, and the instructions executed thereon may be configured for sequential, parallel, and/or distributed processing. Individual components of the logic machine optionally may be distributed among two or more separate devices, which may be remotely located and/or configured for coordinated processing. Aspects of the logic machine may be virtualized and executed by remotely accessible, networked computing devices configured in a cloud-computing configuration.
[0080] Storage machine 512 includes one or more physical devices configured to hold instructions 516 (e.g., search service 112, application program 132, and/or natural language service 150 of FIG. 1) and other data 518 (e.g., schema 114) executable by the logic machine to implement the methods and processes described herein. When such methods and processes are implemented, the state of storage machine 512 may be transformed—e.g., to hold different data.
[0081] Storage machine 512 may include removable and/or built-in devices. Storage machine 512 may include optical memory (e.g., CD, DVD, HD-DVD, Blu-Ray Disc, etc.), semiconductor memory (e.g., RAM, EPROM, EEPROM, etc.), and/or magnetic memory (e.g., hard-disk drive, floppy-disk drive, tape drive, MRAM, etc.), among others. Storage machine 512 may include volatile, nonvolatile, dynamic, static, read/write, read-only, random-access, sequential -access, location-addressable, file-addressable, and/or content-addressable devices.
[0082] It will be appreciated that storage machine 512 includes one or more physical devices. However, aspects of the instructions described herein alternatively may be propagated by a communication medium (e.g., an electromagnetic signal, an optical signal, etc.) that is not held by a physical device for a finite duration.
[0083] Aspects of logic machine 510 and storage machine 512 may be integrated together into one or more hardware-logic components. Such hardware-logic components may include field-programmable gate arrays (FPGAs), program- and application-specific integrated circuits (PASIC / ASICs), program- and application-specific standard products (PSSP /
ASSPs), system-on-a-chip (SOC), and complex programmable logic devices (CPLDs), for example.
[0084] The terms “module,” “program,” and “engine” may be used to describe an aspect of computing system 500 implemented to perform a particular function. In some cases, a module, program, or engine may be instantiated via logic machine 510 executing instructions held by storage machine 512. It will be understood that different modules, programs, and/or engines may be instantiated from the same application, service, code block, object, library, routine, APL function, etc. Likewise, the same module, program, and/or engine may be instantiated by different applications, services, code blocks, objects, routines, APIs, functions, etc. The terms “module,” “program,” and “engine” may encompass individual or groups of executable files, data files, libraries, drivers, scripts, database records, etc.
[0085] It will be appreciated that a “service”, as used herein, may refer to an application program executable across multiple sessions or across multiple user interactions with a search session, including user interactions that occur over multiple discreet periods of time with a search session. A service may be available to one or more system components, programs, and/or other services. In some implementations, a service may run on one or more server- computing devices.
[0086] When included, a display subsystem of input / output subsystem 514 may be used to present a visual representation of data held by storage machine 512. This visual representation may take the form of a graphical user interface (GUI). As the herein described methods and processes change the data held by the storage machine, and thus transform the state of the storage machine, the state of the display subsystem may likewise be transformed to visually represent changes in the underlying data. A display subsystem may include one or more display devices utilizing virtually any type of technology. Such display devices may be combined with logic machine 510 and/or storage machine 512 in a shared enclosure, or such display devices may be peripheral display devices.
[0087] When included, a user input subsystem of input / output subsystem 514 may comprise or interface with one or more user-input devices such as a keyboard, mouse, touch screen, or game controller. In some embodiments, the input subsystem may comprise or interface with selected natural user input (NUT) componentry. Such componentry may be integrated or peripheral, and the transduction and/or processing of input actions may be handled on- or off-board. Example NUI componentry may include a microphone for speech and/or voice recognition; an infrared, color, stereoscopic, and/or depth camera for machine vision and/or gesture recognition, a head tracker, eye tracker, accelerometer, and/or gyroscope for motion detection and/or intent recognition; as well as electric-field sensing componentry for assessing brain activity.
[0088] When included, a communication subsystem of input / output subsystem 514 may be configured to communicatively couple computing system 500 with one or more other computing devices. A communication subsystem may include wired and/or wireless communication devices compatible with one or more different communication protocols. As examples, the communication subsystem may be configured for communication via a wireless telephone network, or a wired or wireless local- or wide-area network. In some embodiments, the communication subsystem may allow computing system 500 to send and/or receive messages to and/or from other devices via a network such as the Internet.
[0089] According to an example disclosed herein, a method performed by a computing system to facilitate multi-round searching comprises: receiving a first search query that includes a first set of one or more search criteria elements; generating first results data based on the first search query, the first results data including a first set of search results in which each search result of one or more search results of the first set of search results identifies: a respective content item, one or more search criteria elements of the first search query satisfied by the content item, and one or more suggested search criteria elements extracted from the content item that are semantically linked to the first set of one or more search criteria elements; receiving a command to catalog a target search result of the first set of search results; adding the target search result to a session-specific catalog of search results responsive to the command; and generating second results data including a second set of search results based on a second search query that includes at least some of the first set of search criteria elements of the first search query and at least one of: the one or more search criteria elements identified by the target search result, the one or more suggested search criteria elements identified by the target search result; wherein the second set of search results includes the target search result and one or more additional search results. In this example or other examples disclosed herein, the second results data is generated based on both: the one or more search criteria elements identified by the target search result, and the one or more suggested search criteria elements identified by the target search result. In this example or other examples disclosed herein, the second results data is generated responsive to selection of a target suggested search criteria element of the one or more suggested search criteria elements identified by the target search result; and the second results data is generated based on the target suggested search criteria element. In this example or other examples disclosed herein, the second results data is generated responsive to receiving the command to catalog the target search result. In this example or other examples disclosed herein, the method further comprises: for each search result of the one or more search results of the first set of search results, extracting each suggested search criteria element from the content item by: identifying a semantic link between a search criteria element of the first search query that is satisfied by the content item and the suggested search criteria element. In this example or other examples disclosed herein, the semantic link is defined by a schema; the search criteria element is defined as an entity within the schema; and the suggested search criteria element is defined as a property of the entity within the schema. In this example or other examples disclosed herein, the semantic link is defined by a schema, the search criteria element is defined as a property of an entity within the schema; and the suggested search criteria element is defined as the entity within the schema.
In this example or other examples disclosed herein, the method further comprises: providing a search criteria element of the first search query to a natural language service; receiving a suggested search criteria element for the search criteria element from the natural language service; and identifying the content item for the first search results data based, at least in part, on the suggested search criteria element being satisfied by the content item. In this example or other examples disclosed herein, the one or more search criteria elements of the first search query include search terms. In this example or other examples disclosed herein, at least some of the first set of search results further identifies one or more search criteria elements of the first search query that are not satisfied by the content item of that search result; and generating the second results data including the second set of search results is based on the first search query excluding the one or more search criteria elements of the first search query that are not satisfied by the target content item. In this example or other examples disclosed herein, the method comprises: outputting, via a user interface, the session-specific catalog including the target search result. In this example or other examples disclosed herein, the method further comprises: sharing the session-specific catalog including the target search result with a target share address or a target user. A computer program is further disclosed herein which, when executed on at least one processor of a computing device or computing system of computing devices, is configured to carry out any of the following example methods or operations thereof.
[0090] According to another example disclosed herein, a computing system comprises: a data storage machine having instructions defining a search service executable by a logic machine to: receive, via a user interface, a first search query that includes a first set of one or more search criteria elements; generate first results data based on the first search query, the first results data including a first set of search results in which each search result of one or more search results of the first set of search results identifies: a respective content item one or more search criteria elements of the first search query satisfied by the content item, and one or more suggested search criteria elements extracted from the content item that are semantically linked to the first set of one or more search criteria elements; output, via the user interface, the first set of search results; receive, via the user interface, a command to catalog a target search result of the first set of search results; add the target search result to a session-specific catalog of search results responsive to the command; generate second results data including a second set of search results based on a second search query that includes at least some of the first set of search criteria elements of the first search query and at least one of: the one or more search criteria elements identified by the target search result, the one or more suggested search criteria elements identified by the target search result; and output, via the user interface, the second set of search results including the target search result and one or more additional search results. In this example or other examples disclosed herein, the instructions including the search service are further executable by the logic machine to: generate the second results data responsive to selection of a target suggested search criteria element of the one or more suggested search criteria elements identified by the target search result; and the second results data is generated based on the target suggested search criteria element. In this example or other examples disclosed herein, the instructions including the search service are further executable by the logic machine to: generate the second results data responsive to receiving the command to catalog the target search result. In this example or other examples disclosed herein, the instructions including the search service are further executable by the logic machine to: for each search result of the one or more search results of the first set of search results, extract each suggested search criteria element from the content item by identifying a semantic link between a search criteria element of the first search query that is satisfied by the content item and the suggested search criteria element. In this example or other examples disclosed herein, the semantic link is defined by a schema of the search service; the search criteria element is defined as an entity within the schema, and the suggested search criteria element is defined as a property of the entity within the schema; or the search criteria element is defined as a property of an entity within the schema and the suggested search criteria element is defined as the entity within the schema. In this example or other examples disclosed herein, the instructions including the search service are further executable by the logic machine to: provide a search criteria element of the first search query to a natural language service; receive a suggested search criteria element for the search criteria element from the natural language service; and identify the content item for the first search results data based, at least in part, on the suggested search criteria element being satisfied by the content item.
[0091] According to another example disclosed herein, a method performed by a computing system to facilitate multi-round searching comprises: receiving a first search query that includes a first set of one or more search criteria elements; generating first results data based on the first search query, the first results data including a first set of search results in which each search result of one or more search results of the first set of search results identifies:
a respective content item, one or more search criteria elements of the first search query satisfied by the content item, and one or more suggested search criteria elements extracted from the content item that are semantically linked to the first set of one or more search criteria elements; receiving selection of a target suggested search criteria element of the one or more suggested search criteria elements of a target search result of the first set of search results; and generating second results data including a second set of search results based on a second search query that includes at least some of the first set of search criteria elements of the first search query and the target suggested search criteria element; the second set of search results including the target search result and one or more additional search results. In this example or other examples disclosed herein, the method further comprises: adding the target search result to a session- specific catalog of search results; and sharing the session-specific catalog of search results including the target search result with a target share address or a target user.
[0092] It will be understood that the configurations and/or approaches described herein are exemplary in nature, and that these specific embodiments or examples are not to be considered in a limiting sense, because numerous variations are possible. The specific routines or methods described herein may represent one or more of any number of processing strategies.
As such, various acts illustrated and/or described may be performed in the sequence illustrated and/or described, in other sequences, in parallel, or omitted. Likewise, the order of the above- described processes may be changed.
[0093] The subject matter of the present disclosure includes all novel and non-obvious combinations and sub-combinations of the various processes, systems and configurations, and other features, functions, acts, and/or properties disclosed herein, as well as any and all equivalents thereof.
Claims (21)
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NL2032064A NL2032064B1 (en) | 2022-06-02 | 2022-06-02 | Multi-round searching and cataloging of search results |
| PCT/US2023/067668 WO2023235733A1 (en) | 2022-06-02 | 2023-05-31 | Multi-round searching and cataloging of search results |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NL2032064A NL2032064B1 (en) | 2022-06-02 | 2022-06-02 | Multi-round searching and cataloging of search results |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| NL2032064B1 true NL2032064B1 (en) | 2023-12-14 |
Family
ID=82019264
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| NL2032064A NL2032064B1 (en) | 2022-06-02 | 2022-06-02 | Multi-round searching and cataloging of search results |
Country Status (2)
| Country | Link |
|---|---|
| NL (1) | NL2032064B1 (en) |
| WO (1) | WO2023235733A1 (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110289080A1 (en) * | 2010-05-19 | 2011-11-24 | Yahoo! Inc. | Search Results Summarized with Tokens |
| US20170242913A1 (en) * | 2016-02-18 | 2017-08-24 | Adobe Systems Incorporated | Analyzing search queries to provide potential search query modifications via interactive user-interfaces |
| US20210149963A1 (en) * | 2019-11-15 | 2021-05-20 | Microsoft Technology Licensing, Llc | Domain-agnostic structured search query exploration |
-
2022
- 2022-06-02 NL NL2032064A patent/NL2032064B1/en active
-
2023
- 2023-05-31 WO PCT/US2023/067668 patent/WO2023235733A1/en unknown
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110289080A1 (en) * | 2010-05-19 | 2011-11-24 | Yahoo! Inc. | Search Results Summarized with Tokens |
| US20170242913A1 (en) * | 2016-02-18 | 2017-08-24 | Adobe Systems Incorporated | Analyzing search queries to provide potential search query modifications via interactive user-interfaces |
| US20210149963A1 (en) * | 2019-11-15 | 2021-05-20 | Microsoft Technology Licensing, Llc | Domain-agnostic structured search query exploration |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023235733A1 (en) | 2023-12-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10572556B2 (en) | Systems and methods for facilitating enhancements to search results by removing unwanted search results | |
| KR102354716B1 (en) | Context-sensitive search using a deep learning model | |
| RU2683507C2 (en) | Retrieval of attribute values based upon identified entries | |
| CN107408130B (en) | Method for searching through indirect cluster connection | |
| US10296538B2 (en) | Method for matching images with content based on representations of keywords associated with the content in response to a search query | |
| US8719246B2 (en) | Generating and presenting a suggested search query | |
| EP3255565A1 (en) | Method and system for evaluating and ranking images with content based on similarity scores in response to a search query | |
| US8798969B2 (en) | Machine learning for a memory-based database | |
| US20140201198A1 (en) | Automatically providing relevant search results based on user behavior | |
| JP2014528134A (en) | Providing topic-based search guidance | |
| US11232153B2 (en) | Providing query recommendations | |
| CN104969223A (en) | Adjacent search results exploration | |
| US9798833B2 (en) | Accessing information content in a database platform using metadata | |
| US11768849B2 (en) | Extensible data platform with database domain extensions | |
| WO2019217214A1 (en) | Personal history recall | |
| EP3912059A1 (en) | System that customizes a re-ranker based upon end user input | |
| NL2032064B1 (en) | Multi-round searching and cataloging of search results | |
| US11429687B2 (en) | Context based URL resource prediction and delivery | |
| US10380163B2 (en) | Domain similarity scores for information retrieval | |
| WO2022005563A1 (en) | Content item summarization with contextual metadata | |
| US20230418873A1 (en) | Query interpreter training with adversarial table perturbations | |
| Mehmeti | ARTIFICIAL INTELLIGENCE THE USE OF KNOWLEDGE GRAPHS | |
| Silveria | Projection: A Mixed-Initiative Research Process | |
| Wang et al. | Personalized search: An interactive and iterative approach | |
| Koskinen | Finding similarities between software development skills |