ENHANCING SEARCH RESULTS WITH SOCIAL LABELS

Abstract

Disclosed herein are systems, methods, and software for facilitating enhanced search services. In an implementation, an enhanced search service receives a search query associated with a user and responsively identifies documents relevant to the search query. The enhanced search service also identifies a social label for each of the documents that is at least partly representative of how the document relates socially to the user. The enhanced search service replies to the search query with search results indicative of at least the documents and the social label for each of the documents.

Description

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of application Ser. No. 14/064,393, filed Oct. 28, 2013, which application is incorporated herein by reference in its entirety.

TECHNICAL FIELD

Aspects of the disclosure are related to computing hardware and software technology, and in particular to search technology and enhanced search services.

TECHNICAL BACKGROUND

Information search services have become ubiquitous in the modern information technology landscape. Through these services, users are able to access a large volume of information in many different ways, ranging from performing general Internet searches to more individual searches of their desktop, mailbox, photos, documents, or other personal information. Users can engage with such services using desktop and laptop computers, tablets, smart phones, gaming devices, or any of a variety of other suitable appliances.

A wide variety of algorithms are employed to find search results that are relevant to a query. The search results are usually ranked in some order related to their relevance to a query. However, why a particular search result is ranked as it is, may not always be apparent to a user. Moreover, as the volume and variety of searchable information expands, it has become increasingly important that search results be presented in a more useful way. Some search services have addressed this concern by accentuating their results and rankings with other information, of which a user's social graph is a prominent example.

A social graph is a data structure that includes information representative of a set of people and their social connections. Social graphs generally include nodes representative of people and edges representative of the connections between them. Other types of nodes can be represented in a social graph, such as documents, projects, and web pages. When a search of a data repository is performed, the search results can be accentuated by taking into account a user's social graph.

In a brief illustration, a user may perform a search of a document repository that returns a set of documents related to a topic. The search results can be accentuated by searching the user's social graph for experts associated with the topic and returning relevant contacts along with the relevant documents for presentation to the user.

In another illustration, a user may perform a web search for a given topic. The search results can be accentuated by showing related endorsements by others in the user's social network. For instance, the user may search for a particular type of restaurant, in response to which a list of restaurants or links to their sites are returned, along with an indication of who in the user's social network “liked” each of the restaurants.

Overview

Provided herein are systems, methods, and software for facilitating enhanced search services. In an implementation, an enhanced search service receives a search query associated with a user and responsively identifies documents relevant to the search query. The enhanced search service also identifies a social label for each of the documents that is at least partly representative of how the document relates socially to the user. In some implementations, the social label for each document may be selected from a set of candidate labels based on an evaluation of each of the candidate labels. The enhanced search service replies to the search query with search results indicative of at least the documents and the social label for each of the documents.

This Overview is provided to introduce a selection of concepts in a simplified form that are further described below in the Technical Disclosure. It should be understood that this Overview 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.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the disclosure can be better understood with reference to the following drawings. While several implementations are described in connection with these drawings, the disclosure is not limited to the implementations disclosed herein. On the contrary, the intent is to cover all alternatives, modifications, and equivalents.

FIG. 1 illustrates a visualization of enhanced search results returned by an enhanced search service in an implementation.

FIG. 2 illustrates an operational scenario involving an enhanced search service in an implementation.

FIG. 3 illustrates a social label process employed by an enhanced search service in an implementation.

FIG. 4 illustrates an operational scenario in an implementation.

FIG. 5 illustrates a social label process employed by an enhanced search service in an implementation.

FIG. 6 illustrates a visualization of relationships in an implementation.

FIG. 7 illustrates candidate labels and a social label in an implementation.

FIG. 8 illustrates a search environment in an implementation.

FIG. 9 illustrates a computing system in an implementation.

TECHNICAL DISCLOSURE

Implementations disclosed herein are directed to social labeling for search results that describes at least one way in which each result is related to a user. In one implementation, such social labeling is supported by an enhanced search service that receives a search query associated with a user. The enhanced search service identifies a set of documents or other types of content in response to the search query. For each document of the set of documents, the enhanced search service identifies a social label that is representative of how the document relates socially to the user. Search results can then be returned to the source of the search that are indicative of the set of documents and the social label for each document.

In a brief illustration, a user may engage in a search by way of any of a variety of search sources. A search query is communicated to an enhanced search service, in response to which the service performs a search of a data repository to identify relevant results, such as a set of documents, web pages, contacts, emails, conversations, meeting invites, or other suitable items.

In addition, the enhanced search service identifies a social label for each item that may express how the item is related to the user. For instance, the social label for any given item may indicate how the user relates to the item. In some scenarios, the relationship between an item and the user is expressed by the social label in terms of another user or users associated with the user. As an example, a social label associated with a document in a set of results may identify a user that recently viewed, modified, or presented the document.

In some implementations, the social label for each item may be selected from a set of potential candidate labels. Selecting the social label from the candidate labels may involve identifying the relationships between the item and users related to the user, such as those in the user's social network, work colleagues, team members, or by some other association. For instance, for a given document, web page, photo, contact, or other item, the enhanced search service analyzes which users have viewed, modified, presented, or otherwise interacted with the item.

Each relationship that is discovered for an item in the search results is then compared to the candidate labels to identify which of the candidate labels relates to, or represents the relationship. It is thus possible for multiple relationships to exist that describe how a given item relates to a user. This may be the case when, for example, multiple other users have interacted with a document or other item, when an individual user has interacted in multiple ways with a given item, or for some other reasons.

Each of the candidate labels can be evaluated based on the relationship or relationships associated therewith to identify which of the candidate labels to use as the social label for a given item. For instance, each candidate label may be scored based on at least a representative trait that is shared in common by each of the candidate labels. The trait may be derived at least in part from a characteristic of each of those of the relationships that relate to each of the candidate labels. Examples of the trait include, but are not limited to, a freshness of each of the candidate labels or a popularity of each of the candidate labels. In still other examples, the strength of a relationship may be considered when evaluating each of the candidate labels. The strength of the relationship may in some situations pertain to how strong the social link is between a person involved in a relationship and the person on behalf of whom a search is being performed. For instance, one candidate label representative how one's boss relates to a document may be chosen as the social label for the document over another candidate label representative of how one's peer or direct report relates to the document. In another scenario, one candidate label representative how one's sibling relates to a document may be chosen as the social label for the document over another candidate label representative of how one's cousin or neighbor relates to the document.

In some implementations, a graph may be queried to identify the relationships between an item, such as a document, and various users. The graph may include nodes representative of documents and possibly other types of items, as well as nodes representative of various users. Edges in the graph may be representative of actions taken by the users with respect to the documents and other items. The relationships considered when selecting the social label for a given result may be representative of the actions taken with respect to each individual document or other items. Thus, relationships between users and search results can be determined by analyzing the nature of the edges connecting search results in the graph to specific users. Examples of possible actions include, but are not limited to, presenting, sharing, creating, modifying, commenting on, viewing, following, and liking a document that is included in a set of search results.

The candidate labels in some scenarios correspond to the various possible actions performed by the users. In such scenarios, the social label identified for the document or other items includes social information that represents at least in part how the document relates socially to the user associated with the search. The social information may describe the relationship in terms of an action taken with respect to the document by at least one various other users related to the user. Examples of the candidate labels include a presented-by label, a shared-by label, a created-by label, a modified-by label, a commented-on-by label, a viewed-by label, a followed-by label, and a liked-by label.

Referring now to the drawings, FIG. 1 illustrates a visualization of enhanced search results. FIG. 2 illustrates an operational scenario involving an enhanced search service that employs a social label process illustrated in FIG. 3. FIG. 4 illustrates another operational scenario involving an enhanced search service and FIG. 5 illustrates another social label process. FIG. 6 illustrates a visualization of various relationships between a document and enterprise users. FIG. 7 illustrates several visualizations of a search result that includes the document in FIG. 6. FIG. 8 illustrates a computing environment in which an enhanced search service may be provided. FIG. 9 illustrates a computing system representative of those suitable for implementing an enhanced search service, such as those illustrated in FIG. 2 and FIG. 4.

Turning to FIG. 1, a visualization 100 of enhanced search results 101 is illustrated. Enhanced search results 101 are representative of search results that may be returned by an enhanced search service employing a social label process in response to a search query. The search query may be initiated by any query source capable of communicating with an enhanced search service. Examples of the query source include computing hardware, software, and any combination or variation thereof. For instance, the query source may be a web page in a browser, a search tool included in an email client, a search tool in a productivity application, a desktop search application, a search tool included in an operating system, a webpage with an embedded search query, or any other search interface to any kind of search engine. In some cases, the search query may be explicitly initiated by user interaction, such as when a user enters a query string into a search box. However, the search query may also be triggered implicitly, such as when a productivity application automatically or programmatically initiates a search for relevant documents, or for any other reason.

Enhanced search results 101 include search result 103, search result 105, and search result 107. Each of the search results identifies one item of various items returned by a search engine, as well as a social label corresponding to each item. Other types of content items in place of or in addition to documents are possible, such as photos, web pages, contacts, or any other type of item that can be identified in search results.

In particular, search result 103 identifies document 113 and a social label 123. Social label 123 includes social information representative of how document 113 relates to a user associated with the search. In this case, document 113, which is named alpha.doc, is identified as having been presented to the user by another person or people. Search result 105 includes document 115 (echo.doc) and social label 125. Social label 125 expresses that document 115 was viewed by another person or people associated with the user. Search result 107 includes document 115 (kilo.doc) and social label 127. Social label 125 includes social information that expresses that document 117 was modified recently by a person or people associated with the user.

Enhanced search results 101 may be presented to the user conducting the search in response to a search query. The social labels 123, 125, and 127 accompanying the documents 113, 115, and 117 in the search results 103, 105, and 107, serve to inform the user about how each item in the enhanced search results 101 relate to the user. For instance, social label 123 informs the user that document 113 was presented to her, social label 125 informs the user that document 115 was viewed by another person, and social label 127 informs the user that document 117 was modified recently by another person. This information may assist the user with navigating the enhanced search results 101 as how an item relates socially to the user may help distinguish one item over another.

FIG. 2 illustrates an operational scenario 200 in which a query source 201 communicates with an enhanced search service 203 to obtain enhanced search results. Enhanced search service 203 employs social label process 300, described in more detail with respect to FIG. 3, to generate the enhanced search results.

In operation, query source 201 communicates a search query to enhanced search service 203. Query source 201 is representative of any source from which a search query may be initiated and to which search results may be returned. Query source 201 may be implemented in hardware, in software, or in some combination thereof. Examples of query source 201 include, but are not limited to, email applications, productivity applications, gaming applications, browser applications, operating system applications, social network applications, and any other suitable application, variation, or combination thereof. Such applications may be provisioned and delivered as locally installed and executed applications, browser-based applications, streamlining applications, or in some other manner. In addition, such applications may be experienced on any of a variety of computing systems, such as desktop, laptop, tablet, and notebook computers, smart phones, gaming machines, or any other physical or virtual system, variation, or combination thereof.

In response to the search query, enhanced search service 203 searches information repository 205 to identify documents or other items relevant to the search query. Enhanced search service 203 is representative of any service capable of receiving search queries and returning enhanced search results. Enhanced search service 203 may be a stand-alone search service or may be integrated with other services. Examples of enhanced search service include, but are not limited to, Internet search services, enterprise search services, desktop search services, file system search services, email search services, image search services, or any other suitable search service, variation of service, or combination thereof. Examples of other services with which enhanced search service 203 may be integrated include, but are not limited to, email services, productivity application services, gaming services, social network services, or any other service, variation, or combination thereof.

Enhanced search service 203 may search information repository 205 using any criteria, algorithm, or other such technology to identify relevant documents, emails, contacts, images, or other content items. A wide variety of search techniques are possible and may be considered within the scope of the present disclosure. Information repository 205 is representative of any collection of searchable information, such as a collection of documents, emails, images, web pages, blog posts, text messages, or the like. It may be appreciated that information repository 205 may include other information, such as an index or a graph, to facilitate a search of the content items included therein. Information repository 205 may be a stand-alone repository dedicated to enhanced search service 203 or it may be implemented in an integrated manner with another service or services. Examples of information repository 205 include, but are not limited to, an email mailbox, an Internet search index, an enterprise information storage facility, a document storage facility, an information backup facility, or any other suitable collection of searchable information. Information repository 205 may be implemented on any physical or virtual computing system or collection of computing systems, as well as on any variation or combination thereof.

Upon identifying a set of relevant documents or other content items, enhanced search service 203 employs social label process 300, discussed below with respect to FIG. 3, to identify a social label for each of the set of relevant documents. Enhanced search service 203 returns search results to query source 201 that are indicative of the relevant documents and the social labels associated therewith. Query source 201 may then display the search results to a user associated with the search such that the user can view, navigate, and potentially select one of the documents or other content items from the results. As mentioned above, the social labels included with the search results may assist the user in distinguishing one item form another, thereby enhancing the search experience.

Social label process 300, illustrated in FIG. 3, is representative of any process that enhanced search service 203 may employ to determine which social labels to associate and return with various search items in a set of search results. In operation, documents or other content items are identified within the context of a search process employed by enhanced search service 203 in response to a search query (step 301). For each document (or other type of item) that is identified, one or more candidate labels associated with each document are identified that represent the various ways in which each document may related to the user associated with the search (step 303).

In a brief illustration, a document that is returned by a search process may be related to the user in multiple ways. For instance, a person associated with the user may have recently presented the document to the user, while another person may have recently viewed the document. As such, two candidate labels may be generated that correspond to both relationships. It may be appreciated that a variety of relationships are possible, and thus so are a variety of candidate labels, and the scope of the present disclosure is not restricted to just those disclosed herein. The two candidate labels are then evaluated to determine which one to put forth as the social label for the document. The candidate labels may be evaluated based on any suitable criteria, such as the recentness of the relationships associated with each candidate label, a weight given to each type of relationship, a frequency of the relationship, and so on. In some examples, the strength of a relationship may be considered when evaluating each of the candidate labels. The strength of a social link between a person represented in a candidate label and the user associated with the search may be considered. For instance, one candidate label representative how one's manager relates to a document may be chosen as the social label for the document over another candidate label representative of how one's distant peer relates to the document. In another scenario, one candidate label representative how one's close relative relates to a document may be chosen as the social label for the document over another candidate label representative of how one's distant relative relates to the document. In any case, a social label is then selected from the candidate labels based on the evaluation (step 305).

This analysis and evaluation may be carried out for each document that is returned as part of the search, at the end of which a set of documents and a set of corresponding social labels for the documents are assembled. Search results indicative of the documents and their social labels are returned to query source 201 for consideration by the user. In some scenarios, the actual documents or other content items may be returned as part of the search results. However, in many implementations merely an indication of the documents will be returned. For example, a link to each document, an icon representative of each document, or some other indication of each document will be returned. The social labels as identified in the search results may include social information that describes how each document is related to the user. Other types of descriptive data may also be included, such as images of people, color coding, and the like.

FIG. 4 illustrates another operational scenario 400 in an implementation. In operational scenario 400, query source 401 communicates a search query to enhanced search service 402. Enhanced search service 402 includes a service interface 403, a search engine 405, a social label engine 409, and a results integrator 411. Information repository 407 is illustrated as external to enhanced search service 402, although it may be integrated with enhanced search service 402 in some implementations. In addition, graph service 415 and graph 417 are illustrated as external to enhanced search service 402, although they too could be integrated with it in some implementations.

Service interface 403 receives the search query from query source 401 and communicates it to search engine 405 for processing. Query source 401 is representative of any source from which a search query may be initiated and to which search results may be returned. Query source 401 may be implemented in hardware, in software, or in some combination thereof. Service interface 403 is representative of any interface to search engine 405 capable of receiving search queries, communicating them to search engine 405, and communicating enhanced search results to query source 401. Service interface 403 may be a stand-alone element or may be integrated with other elements of enhanced search service 402. In addition, service interface 403 may be implemented in hardware, in software, or in some variation or combination thereof.

Search engine 405 searches information repository 407 for any information items that may be relevant to the search query. Search engine 405 is representative of any search engine capable of searching information repository 407. Examples include Internet search engines, email search engines, document search engines, desktop search engines, file system search engines, social network search engines, or any other type of search facility, variation, or combination thereof. Search engine 405 may be implemented in hardware, software, or any variation or combination thereof.

Information repository 407 is representative of any collection of information that may be searched by search engine 405. Information repository 407 may include various documents, photos, contacts, emails, or other content items. Information repository 407 may also include an index to the items, although search engine 405 may maintain an index independently. A variety of information repositories 407 are possible and may be considered within the scope of the present disclosure.

In this scenario, it is assumed for exemplary purposes that search engine 405 identifies documents in information repository 407 that satisfy the search query. Search engine 405 identifies the documents to results integrator 411 such that the documents, or an indication thereof, may be included in enhanced search results.

Social label engine 409 is also made aware of which documents were found to be relevant to the search query. Social label engine 409 is representative of any service capable of identifying social labels for documents found to be relevant to a search query. Social label engine 409 may be implemented in hardware, in software, or in some variation or combination thereof.

While illustrated as coming from information repository 407, it may be search engine 405 or results integrator 411 that communicates with social label engine 409 to identify the relevant search results. In any case, social label engine 409 employs social label process 500, discussed below with respect to FIG. 5, to identify social labels for each of the relevant documents. As part of this process, social label engine 409 considers relationships that are monitored by graph service 415 and maintained in graph 417. The relationships may be between, for example, the relevant documents and various users that are also related to the user associated with the search.

In particular, graph service 415 monitors information repository 407 or services associated with for interactions with the various documents and other content items stored therein. For example, graph service 415 can monitor a document for when a user views, modifies, shares, or presents the document. The various interactions with the various documents on behalf of users may be considered events that are represented in graph 417.

Graph 417 includes nodes and edges representative of the documents, people, and relationships between them that are created when events occur. For example, graph 417 may include a node representative of a document and several other nodes representative of various people in an enterprise. The edges between them would then represent the various actions that the people may take with respect to the document. Graph service 415 may be implemented in a variety of ways that may be considered within the scope of the present disclosure. In other words, how graph service 415 operates and the structure or nature of graph 417 is not intended to limit the scope of the present disclosure.

Having identified a social label for each of the relevant documents, social label engine 409 communicates the social labels to results integrator 411. Results integrator 411 generates search results indicative of the relevant documents and the social labels associated with the relevant documents. Results integrator 411 is representative of any element or collection of elements capable of integrating documents identified by a search with corresponding social labels to generate enhanced search results. Results integrator 411 may be implemented in hardware, in software, or in some variation or combination thereof.

Results integrator 411 communicates the search results, which includes at least an indication of the documents and the social labels, to service interface 403. Service interface 403 then communicates the search results to query source 401. Query source 401 may then present the enhanced search results or otherwise process them such that the user associated with the search may consider the enhanced results.

FIG. 5 illustrates social label process 500 that may be employed by social label engine 409 to identify social labels for the various documents found to be relevant to a search query. In operation, social label engine 409 identifies the relationship or relationships that may exist between the relevant documents and the user associated with the search (step 501). Social label engine 409 may accomplish this by querying graph 417 for any edges that relate a given document in the set of relevant documents to the user by way of other users linked to the user, but also possibly by a direct relationship. This step is repeated for each document in the set such that one or more relationships are returned for each document.

Next, social label engine 409 determines for each document in the set of relevant documents which of the relationships relate to which of a pool of candidate labels (step 503). In an example, for a document that returned just one relationship, just one candidate label will be identified. However, for another document in the set that return two or more relationships, two or more candidate labels may be identified. In some scenarios, the number of candidate labels may match the number of relationships found for a document, while in other scenarios the number of candidate labels may not match the number of relationships. For example, a given document may return four different relationships, two of which are the same kind of relationship. In such a scenario, social label engine 409 would identify three distinct candidate labels from which to select the social label.

Having identified the candidate social labels, social label engine 409 evaluates each of the candidate social labels based on the relationship or relationships associated therewith (step 505). This may include, for example, assessing the age or freshness of a given relationship. This may be accomplished by time-stamping each edge in graph 417 such that the age of the corresponding relationships can be ascertained. In another example, the popularity of a given candidate label may be assessed. For example, a candidate label that has several relationships associated with it may be given a greater weight than another candidate label that has relatively fewer relationships associated with it. Other criteria include the identity of the other person or people associated with a given relationship. In some examples, the strength of a social link between a person represented in a candidate label and the user associated with the search may be considered, such as when any candidate label corresponding to a relationship associated with a high ranking person may be given priority over a candidate label associated via a relationship with a relatively lower ranking person. Many other criteria for evaluating the candidate labels are possible and may be considered within the scope of the present disclosure.

The social label for each document in the set of relevant documents is selected from the candidate labels for each document based on the evaluation discussed above (step 507). A scoring process or some other technique may be used to weight each candidate label in the evaluations. The candidate label having the highest score may then be used as the social label for a document. In some implementations it may be possible to use multiple social labels for a single document, although it is assumed for the sake of clarity that a single social label is selected for each individual document.

FIG. 6 illustrates a visualization 600 of various relationships that may be established between a document 601 and users 611, 612, 613, 614, 615, 616, 617, and 618 in an enterprise. The relationships depicted in visualization 600 may be captured by a graph service, such as graph service 415, as events occur within an enterprise. An enterprise graph may be maintained by the graph service in which the events may be stored or otherwise reflected. A social label engine, such as social label engine 409, may access the graph to identify relationships for documents in a set of documents returned by a search engine. Candidate labels may be derived from and evaluated based on the relationships in order to select a social label for each of the relevant documents.

Document 601 is representative of any type of document with respect to which users may perform actions and otherwise interact. Examples of document 601 include, but are not limited to, word processing documents, spreadsheets and workbooks, drawings, and presentations, as well as any other type of document. While visualization 600 makes reference to document 601, it may be appreciated that such a visualization may apply as well to other types of content items, such as photos, music files, video files, blog posts, text messages, images, and contacts, as well as any other type of item with which relationships may be established by virtue of user interactions.

In visualization 600, document 601 has been interacted with in a variety ways by a variety of people. In particular, user 611 has viewed document 601. User 612 has viewed document 601 twice and presented it once. User 613 has presented document 601 and user 614 has modified it. User 615 has presented and viewed document 601. User 616 commented on document 601 and user 617 created it. Lastly, user 618 both modified and commented on document 601.

As mentioned, the relationships visualized in FIG. 6 may be stored in a graph and can be used by a social label engine to generate candidate labels and ultimately a social label for document 601. FIG. 7 illustrates several exemplary candidate labels that may be generated with respect to document 601. The candidate labels may then be evaluated to pick a social label for document 601.

In candidate label 701, social information included therein describes how the document relates to the user that initiated the search. In particular, candidate label expresses that document 601 was commented on by William on November 13^th. Candidate label 703 expresses that document 601 was viewed by three people. Candidate label 705 expresses that document 601 was presented to James by Sarah on July 11^th. Candidate label 708 expresses that document 601 was created by Kristin. Other candidate labels in addition to or in place of those disclosed herein are possible and may be considered within the scope of the disclosure.

It may be appreciated from candidate labels 701, 703, 705, and 707 that a wide variety of candidate labels are possible and may be considered within the scope of the present disclosure. In addition, a wide variety of social information may be presented within the candidate labels. The social label may be selected based on a wide variety of weighting criteria and other factors that are evaluated when selecting a social label. It is assumed for exemplary purposes in FIG. 7 that candidate label 705 is selected to be the social label for 601 in a set of search results returned to a user.

Accordingly, FIG. 7 includes an example of an enhanced search result 709. Enhanced search result 709 includes a content portion 711 that includes an icon representative of document 601 and its name, “Report.doc.” Enhanced search result 709 also includes social label 705. Thus, it may be evident in from enhanced search result 709 that document 601 was presented to James by Sarah on July 11. This social information may be useful to the user associated with the search when navigating through various search results. In the aggregate, if others of the search results are also enhanced by way of a social label, the user is able to compare their relative social information, which may further assist with navigating what can be an overwhelming volume of search results.

FIG. 8 illustrates a search environment 800 that is representative of any environment in which the various implementations of an enhanced search service discussed herein may be carried out. Search environment 800 includes communication network 810 over which computing systems 801, 803, and 805 may communicate with computing system 807 and with computing system 809. Computing system 807 and computing system 809 may also communicate with each other over communication network 810 or over some other communication link or collection of links.

Examples of computing systems 801, 803, and 805 include, but are not limited to, desktop computers, work stations, laptop computers, notebook computers, tablet computers, mobile phones, personal digital assistances, media devices, gaming devices, and any other physical or virtual computing machine or combinations and variations thereof. Computing systems 801, 803, and 805 may be capable of implementing search sources 811, 813, and 815 respectively. Search sources 811, 813, and 815 may each be representative of any hardware, software, or combinations thereof capable of providing an interface to enhanced search service 817 such that users can interact with computing systems 801, 803, and 805 to perform searches. Examples of search sources 811, 813, and 815 include, but are not limited to, a search engine web page, a search engine tool integrated into another application (such as an email client or productivity application), a desktop search tool, a mobile search tool, or any other suitable search source.

Computing system 807 may be any computing system or collection of computing systems capable of implementing enhanced search service 817, which is representative of any enhanced search service, including enhanced search services 203 and 402. Computing system 809 may also be any computing system or collection of systems capable of implementing graph service 819. Graph service 819 is optional and may be excluded in some implementations. Examples of computing system 807 and computing system 809 include server computers, cloud computing platforms, data center equipment, physical or virtual computing machines, and any variation or combination thereof.

Computing system 900 is representative of any computing system suitable for implementing any of computing systems 801, 803, 805, 807, and 809, although the discussion below makes specific reference to computing system 807 for purposes of clarity. In addition, while enterprise search service 817 is illustrated as implemented separately from a search interface, or remotely from the devices with which a user may interact, it may be appreciated that in some implementations all or portions of enterprise search service 817 may be implemented locally with respect to a user, such as in a co-located fashion on a device operated by a user, of which computing systems 801, 803, and 805 are representative.

In operation, computing systems 801, 803, and 805 may communicate with computing system 807 to perform information searches. This may include communicating search requests to and receiving search replies from enhanced search service 817. Enhanced search service 817 handles the search requests in accordance with the various implementations described herein for enhanced search services 203 and 402.

In addition, computing systems 801, 803, and 805 may communicate from time to time with computing system 809 in the context of facilitating graph service 819. Computing system 801, 803, and 805 may communicate with other services that may be separate from enhanced search service 817 or that may include enhanced search service 817 therein, such as such as productivity application services, file storage services, email services, chat services, blog services, voice and video calling services, or any other type of application service. Some or all of the application services may be implemented locally or in part with respect to computing systems 801, 803, and 805. Within the context of these services, events may occur that can be captured and from which an enterprise graph or graphs may be constructed. Graph service 819 may capture the events and construct the graph, although in some implementations these tasks may be allocated to another service or services.

Communication between any of the elements contemplated in FIG. 8 may occur in accordance with various communication protocols, such as the Internet protocol (IP, IPv4, IPv6, etc.), the transfer control protocol (TCP), and the user datagram protocol (UDP), as well as any other suitable communication protocol, variation, or combination thereof. Communication network 810 may be representative of a network or collection of networks over which the elements contemplated in FIG. 8 may exchange information, such as an intranet, the Internet, a local area network, a wide area network, a wireless network, a wired network, a virtual network, a software defined network, or any combination or variation thereof. Communication network 810 may include connections, devices, and communication media, such as metal, glass, air, or any other suitable communication media over which information may be exchanged. The aforementioned communication media, networks, connections, protocols, and devices are well known and need not be discussed at length here.

In any of the aforementioned examples in which information is exchanged at least between search sources 811, 813, and 815 and enhanced search service 817, the exchange of information may occur in accordance with any of a variety of protocols, including FTP (file transfer protocol), HTTP (hypertext transfer protocol), REST (representational state transfer), Web Socket, DOM (Document Object Model), HTML (hypertext markup language), CSS (cascading style sheets), HTML5, XML (extensible markup language), JavaScript, JSON (JavaScript Object Notation), and AJAX (Asynchronous JavaScript and XML), as well as any other suitable protocol, variation, or combination thereof.

Referring now to FIG. 9, computing system 900 is representative of any computing system or collection of systems suitable for implementing all or portions of enhanced search service 817 and optionally any of the other operational scenarios and examples described herein. In the aggregate, a collection of systems such as computing system 900 may provide an enhanced search service on a large scale to many users. For example, computing system 900 may be representative of any system used in a physical or virtual data center or collection of data centers to provide an enhanced search service at a very large scale to millions of users or at even greater scale. However, smaller scale implementations at the enterprise, university, school, family, or individual size, for example, are also possible and may be considered within the scope of this disclosure.

Computing system 900 may be implemented as a single apparatus, system, or device or may be implemented in a distributed manner as multiple apparatuses, systems, or devices. Examples of computing system 900 include server computers, rack servers, blade servers, cloud computing platforms, and data center equipment, as well as any other type of physical or virtual server machine, and any variation or combination thereof. While typically implemented in a server or collection of servers, enhanced search service 817 may also be implemented all or in part on desktop computers, laptop computers, tablet computers, notebook computers, mobile computing devices, cell phones, media devices, and gaming devices, as well as any other type of physical or virtual computing machine and any combination or variation thereof, of which computing system 900 may also be representative.

Computing system 900 includes, but is not limited to, processing system 901, storage system 903, software 905, communication interface system 907, and user interface system 909, which is optional. Processing system 901 is operatively coupled with storage system 903, communication interface system 907, and user interface system 909. Processing system 901 loads and executes software 905 from storage system 903. When executed by processing system 901, software 905 directs processing system 901 to operate as described herein for enhanced search service 203, enhanced search service 402, social label process 300, social label process 500, and any of the operational scenarios and examples disclosed herein. Computing system 900 may optionally include additional devices or functionality not discussed for purposes of brevity.

Referring still to FIG. 9, processing system 901 may comprise a microprocessor and other circuitry that retrieves and executes software 905 from storage system 903. Processing system 901 may be implemented within a single processing device but may also be distributed across multiple processing devices or sub-systems that cooperate in executing program instructions. Examples of processing system 901 include general purpose central processing units, application specific processors, and logic devices, as well as any other type of processing device, combinations, or variations thereof.

Storage system 903 may comprise any computer readable storage media readable by processing system 901 and capable of storing software 905. Storage system 903 may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable program instructions, data structures, program modules, or other data. Examples of storage media include random access memory, read only memory, solid state memory, magnetic disks, optical disks, flash memory, virtual memory and non-virtual memory, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other suitable storage media. In no case is the computer readable storage media a propagated signal.

In addition to computer readable storage media, in some implementations storage system 903 may also include computer readable communication media over which software 905 may be communicated internally or externally. Storage system 903 may be implemented as a single storage device but may also be implemented across multiple storage devices or sub-systems co-located or distributed relative to each other. Storage system 903 may comprise additional elements, such as a controller, capable of communicating with processing system 901 or possibly other systems.

Software 905 may be implemented in program instructions and among other functions may, when executed by processing system 901, direct processing system 901 to operate as described herein for social label process 300 or social label process 500 and their variations, and optionally as described with respect to the various operational scenarios and examples disclosed herein. In particular, the program instructions may include various components or modules that cooperate or otherwise interact to carry out social label process 300 or social label process 500. The various components or modules may be embodied in compiled or interpreted instructions or in some other variation or combination of instructions. The various components or modules may be executed in a synchronous or asynchronous manner, serially or in parallel, in a single threaded environment or multi-threaded, or in accordance with any other suitable execution paradigm, variation, or combination thereof. Software 905 may include additional processes, programs, or components, such as operating system software or other application software. Software 905 may also comprise firmware or some other form of machine-readable processing instructions executable by processing system 901.

In general, software 905 may, when loaded into processing system 901 and executed, transform a suitable apparatus, system, or device (of which computing system 900 is representative) overall from a general-purpose computing system into a special-purpose computing system customized to facilitate enhanced search services as described herein for each implementation. Indeed, encoding software 905 on storage system 903 may transform the physical structure of storage system 903. The specific transformation of the physical structure may depend on various factors in different implementations of this description. Examples of such factors may include, but are not limited, to the technology used to implement the storage media of storage system 903 and whether the computer-storage media are characterized as primary or secondary storage, as well as other factors.

For example, if the computer readable storage media are implemented as semiconductor-based memory, software 905 may transform the physical state of the semiconductor memory when the program instructions are encoded therein, such as by transforming the state of transistors, capacitors, or other discrete circuit elements constituting the semiconductor memory. A similar transformation may occur with respect to magnetic or optical media. Other transformations of physical media are possible without departing from the scope of the present description, with the foregoing examples provided only to facilitate this discussion.

Referring again to FIG. 2 and FIG. 4, through the operation of a computing system or systems of which computing system 900 is representative, transformations may be performed with respect to search results identified in response to a search query. As an example, a set of search results may include various documents. The set of search results may be modified from a first state in which there are no associated social labels, to a second state in which social labels are identified and included with the search results. When presented to a user, a visualization of the search results is enhanced by the social labels.

It should be understood that computing system 900 is generally intended to represent a computing system or systems on which software 905 may be deployed and executed in order to implement enhanced search service 203 or enhanced search service 402, and optionally all or portions of the various operational scenarios and examples described herein. However, computing system 900 may also be suitable as any computing system on which software 905 may be staged and from where software 905 may be distributed, transported, downloaded, or otherwise provided to yet another computing system for deployment and execution, or yet additional distribution.

Communication interface system 907 may include communication connections and devices that allow for communication with other computing systems (not shown) over a communication network or collection of networks (not shown). Examples of connections and devices that together allow for inter-system communication may include network interface cards, antennas, power amplifiers, RF circuitry, transceivers, and other communication circuitry. The connections and devices may communicate over communication media to exchange communications with other computing systems or networks of systems, such as metal, glass, air, or any other suitable communication media. The aforementioned media, connections, and devices are well known and need not be discussed at length here.

Communication between computing system 900 and any other computing system (not shown) may occur over a communication network or networks and in accordance with various communication protocols, combinations of protocols, or variations thereof. Examples of communication networks over which computing system 900 may exchange information with other computing systems include intranets, the Internet, local area networks, wide area networks, wireless networks, wired networks, virtual networks, software defined networks, or any combination or variation thereof. The aforementioned communication networks and protocols are well known and need not be discussed at length here.

When applicable, user interface system 909 may include a keyboard, a mouse, a voice input device, a touch input device for receiving a touch gesture from a user, a motion input device for detecting non-touch gestures and other motions by a user, and other comparable input devices and associated processing elements capable of receiving user input from a user. Output devices such as a display, speakers, haptic devices, and other types of output devices may also be included in user interface system 909. In some cases, the input and output devices may be combined in a single device, such as a display capable of displaying images and receiving touch gestures. The aforementioned user input and output devices are well known in the art and need not be discussed at length here.

User interface system 909 may also include associated user interface software executable by processing system 901 in support of the various user input and output devices discussed above. Separately or in conjunction with each other and other hardware and software elements, the user interface software and user interface devices may support a graphical user interface, a natural user interface, or any other type of user interface. For example, a search interface to an enhanced search service may be presented through user interface system 909. In another example, search results returned from an enhanced search service that include social labels, may be presented through user interface system 909.

The functional block diagrams, operational scenarios and sequences, and flow diagrams provided in the Figures are representative of exemplary systems, environments, and methodologies for performing novel aspects of the disclosure. While, for purposes of simplicity of explanation, methods included herein may be in the form of a functional diagram, operational scenario or sequence, or flow diagram, and may be described as a series of acts, it is to be understood and appreciated that the methods are not limited by the order of acts, as some acts may, in accordance therewith, occur in a different order and/or concurrently with other acts from that shown and described herein. For example, those skilled in the art will understand and appreciate that a method could alternatively be represented as a series of interrelated states or events, such as in a state diagram. Moreover, not all acts illustrated in a methodology may be required for a novel implementation.

The included descriptions and figures depict specific implementations to teach those skilled in the art how to make and use the best option. For the purpose of teaching inventive principles, some conventional aspects have been simplified or omitted. Those skilled in the art will appreciate variations from these implementations that fall within the scope of the invention. Those skilled in the art will also appreciate that the features described above can be combined in various ways to form multiple implementations. As a result, the invention is not limited to the specific implementations described above, but only by the claims and their equivalents.

Claims

1. A method, comprising:

receiving a search query from a computing device, the computing device associated with a first user;

identifying a document in response to the search query;

determining a first relationship between the document and a second user, the first relationship representing an interaction between the document and the second user;

comparing the first relationship to one or more candidate social labels to identify a candidate social label that specifies a second relationship matching the first relationship, wherein each identified candidate social label specifies the interaction with the document; and

causing a search result to be transmitted to the first computing device, the search result comprising a respective identified candidate social label and the document or an indication of the document.

2. The method of claim 1, wherein determining the first relationship comprises identifying the first relationship between the document and a plurality of second users based on a graph that includes information representative of documents and users.

3. The method of claim 2, wherein the graph comprises:

a plurality of nodes representative of documents and a plurality of users, the plurality of users including the first user and the second user; and

edges connected between the plurality of nodes, each edge representing an interaction between the document and a respective user in the plurality of users.

4. The method of claim 3, wherein each interaction comprises one of presenting the document, sharing the document, creating the document, modifying the document, commenting on the document, viewing the document, following the document, or liking the document.

5. The method of claim 3, wherein each of the one or more candidate social labels corresponds to a respective interaction with the document.

6. The method of claim 5, wherein each of the one or more candidate social labels comprises one of:

a presented-by label representative of the second user having presented the document;

a shared-by label representative of the second user having shared the document;

a created-by label representative of the second user having created the document;

a modified-by label representative of the second user having modified the document;

a commented-on-by label representative of the second user having commented on the document;

a viewed-by label representative of the second user having viewed the document;

a followed-by label representative of the second user having followed the document; or

a liked-by label representative of the second user having liked the document.

7. The method of claim 1, wherein the document is one of a word processing document, a spreadsheet, a workbook, a drawing, or a presentation document.

8. The method of claim 1, wherein each identified candidate social label for the document comprises information that represents at least in part how the document relates to the first user in terms of the interaction taken by the second user.

9. The method of claim 1, wherein at least one identified candidate social label further identifies the second user.

10. The method of claim 1, wherein at least one identified candidate social label further identifies the first user.

11. A computer readable storage media storing instructions, that when executed by a processing system, causes operations to be performed, the operations comprising:

receiving a search query from a computing device, the computing device associated with a first user;

identifying a document in response to the search query;

determining a first relationship between the document and a second user, the first relationship representing an interaction between the document and the second user;

comparing the first relationship to one or more candidate social labels to identify at least one candidate social label that specifies a second relationship that matches the first relationship, wherein each identified candidate social label specifies the interaction with the document;

scoring each identified candidate social label based on a representative trait shared in common by each of the candidate social labels; and

based on the scoring, causing a search result to be transmitted to the computing device, the search result comprising a respective identified candidate social label and the document or an indication of the document.

12. The computer readable storage media of claim 11, wherein the representative trait is derived at least in part from a characteristic of one or more second relationships.

13. The computer readable storage media of claim 11, wherein the representative trait comprises a freshness of each candidate social label.

14. The computer readable storage media of claim 11, wherein the representative trait comprises a popularity of each candidate social label.

15. The computer readable storage media of claim 11, wherein the representative trait comprises a strength of the second relationship specified by the identified candidate social label.

16. The computer readable storage media of claim 15, wherein the strength of the second relationship is associated with a higher ranking second user over a lower ranking second user.

17. The computer readable storage media of claim 15, wherein the strength of the second relationship comprises a strength of a link between the identified candidate social label and the first user.

18. The computer readable storage media of claim 11, wherein scoring each identified candidate social label includes a weighting of a respective relationship associated with each identified candidate social label.

19. A system, comprising:

a processing system; and

a storage system storing instructions, that when executed by the processing system, causes operations to be performed, the operations comprising: receiving a search query from a computing device that is associated with a first user; identifying a document in response to the search query; determining a first relationship between the document and a second user, the first relationship representing an interactions with the document by the second user; comparing the first relationship to one or more candidate social labels to identify a candidate social label that specifies a second relationship matching the first relationship, wherein each identified candidate social label identifies the second user and specifies the interaction with the document; and causing a search result to be transmitted to the computing device, the search result comprising a respective identified candidate social label and the document or an indication of the document.

20. The system of claim 19, wherein the respective identified candidate social label further identifies the first user.