Topicality Scores, Social Scores and User-Generated Content At Google

Just What is a Topicality Score?

Topicality Scores give you an idea of what content on a webpage is about – what the topical subject of that page might be.  And they provide a way for Google to rank pages based on those topicality scores.

A recent Google patent about searching was just published and looks at Topicality Scores, Social Scores, and User Generated Content.

I have written about topicality scores at Google before.   The latest post was:  Topical Search Results at Google?

Search engines identify resources (e.g., images, audio, video, web pages, text, documents) relevant to a searcher’s needs and present information about the resources in a most helpful manner.

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Search engines return search results in response to a searcher-submitted text query.

In response to an image search text query, the search engine returns a set of search results identifying resources responsive to the query.

A large number of search results can get returned for a given query.

It can get difficult for a searcher to choose the most relevant result or provide advice that the searcher is comfortable relying on.

A searcher may give more weight to search results associated with reviews, opinions, or other content related to the searcher’s social graph (e.g., contacts of the searcher) and other searchers.

These search results can get clouded by content associated with other searchers.  This may be when a search engine will look at Topicality Scores to better understand what those pages and the information on them are about.

Technologies For Searching

This patent describes technologies for searching, including topicality scores.

In general,  the subject matter from this patent includes:

• Receiving a search query
• Identifying potential search results responsive to the search query, the potential search results corresponding to digital content stored in computer-readable storage media
• Deciding that the potential search results include user-generated content that gets generated using computer-implemented social services
• Retrieving data associated with the searcher-generated content, the data including scores
• Choosing, based on the scores, that the searcher-generated content is to get provided as a search result
• In generating SERPs, the search results include web-based search results and at least a portion of the searcher-generated content.
• Transmitting the search results to a client computing device for display to the searcher

These  can include the following features:

Topicality Scores

• Determining a topicality score associated with the searcher-generated content is greater than or equal to threshold topicality scores, the topicality score being included in the scores, where determining that the searcher-generated content is to get provided as a search result occurs in response to determining that the topicality score associated with the searcher-generated content is greater than or equal to the threshold topicality score;
• The topicality score indicates the degree to which the searcher-generated content pertains to the search query
• And The topicality score indicates the degree to which the searcher-generated content relates to a matter of interest
  Actions further include determining that the searcher-generated content is recently generated content, wherein determining that the topicality score associated with the searcher-generated content is greater than or equal to the threshold topicality score occurs in response to determining that the searcher-generated content is recently generated content

Trending Search Queries

• Deciding that the search query is a trending search query

User-Generated Content

• Having the searcher-generated content is recently generated content, wherein determining that the topicality score associated with the searcher-generated content is greater than or equal to the threshold topicality score occurs in response to determining that the search query is a trending search query and determining that the searcher-generated content is recently generated content.

An Overall Score

• Choosing that an overall score associated with the searcher-generated content is greater than or equal to an overall threshold score; the overall score gets included in the data, wherein determining that the searcher-generated content is to get provided as a search result occurs in response to determining that the overall score associated with the searcher-generated content is greater than or equal to the overall threshold score; actions further include determining that the search query is not a trending search query, wherein determining that the overall score associated with the searcher-generated content is greater than or equal to the overall threshold score occurs in response to determining that the search query is not a trending search query. The score reflects the quality of the searcher-generated content and the relevance of the searcher-generated content to the searcher

A Digital Image

• Picking that the searcher-generated content comprises a digital image
• Noting that the digital image is to get displayed within an image search results portion of the search results; actions further include determining that the searcher-generated content is without text associated with the digital image, wherein determining that the digital image is to get displayed within the image search results portion of the search results occurs in response to determining that the searcher-generated content is without text associated with the digital image; the searcher-generated content includes content generated by the searcher;

User-Generated Content Generated by An Author User

• The searcher-generated content comprises content generated by an author user; the author user is a member of a social graph of the searcher; the searcher-generated content includes at least one an electronic message, text provided in a chat session, a post to a social networking service, a digital image; and the social computer-implemented services include at least one of:
• Social networking services,
• Electronic messaging service
• Chat service
• Micro-blogging service
• Blogging service
• Digital content sharing service.

This recently granted patent is at:

Selective presentation of content types and sources in search
Inventors: Daniel Belov, Matthew E. Kulick, Adam D. Bursey, David Yen, and Maureen Heymans
Assignee: GOOGLE LLC
US Patent 11,288,331
Granted: March 29, 2022
Filed: May 15, 2019

Abstract

Implementations of the present disclosure include actions of receiving a search query, identifying potential search results responsive to the search query, the potential search results corresponding to digital content stored in computer-readable storage media, determining that the potential search results include user-generated content that is generated using computer-implemented social services, receiving data associated with the user-generated content, the data including scores, determining, based on the scores, that the user-generated content is to be provided as a search result, generating search results, the search results including web-based search results and at least a portion of the user-generated content, and transmitting the search results to a client computing device for display to the searcher.

Aspects of this specification are directed to retrieving and displaying searcher-generated content in search results.

Searcher-generated content can include content that is generated using social computer-implemented services.

Social Computer-Implemented Services

Example social computer-implemented services can include:

• Social networking service
• Electronic messaging service
• Chat service
• Micro-blogging service
• Blogging service
• Digital content sharing service

User-Generated Content

The user-generated content can include:

Content provided in:

• Electronic messages
• Chat sessions
• Posts to social networking services
• Content posted to sharing services (e.g., photo sharing services)
• Content posted to a blogging service.

For purposes of illustration, and by way of non-limiting example, implementations of the present disclosure will get discussed in the context of digital content generated and distributed by searchers of social networking services.

The present disclosure can be applied to other content types including, for example, electronic message content and chat content.

Search results can get generated based on a search query provided by a searcher. The search results can include publicly available content. The search results can consist of searcher-generated content. Searcher-generated content provides a range that the searcher and other searchers generate. Whether and how the searcher-generated content is displayed in the search results can get determined based on the characteristics of the searcher-generated content

Access Controlled Content

Searcher-generated content can include content that is access controlled. Access controlled content can consist of content that is associated with privacy settings such that only select users can access the content. Example access-controlled content can include content provided in electronic messages, chat sessions, and posts to social networking services. For example, an electronic message can have privacy settings.

The content of the electronic message is only accessible to the author of the electronic message and the recipients to whom the electronic message was sent to. As another example, a chat session can have privacy settings such that the content of the chat session is only accessible to the participants in the chat session. As another example, a post to a social networking service can have privacy settings such that the content of the post is only accessible to the author of the bar and to searchers whom the author has allowed access.

Author Users Associated With A Particular Searcher Can Get Identified Using A Social Graph

Author users associated with a particular searcher can bget identified using a social graph of the searcher. A social graph can refer to a single social chart or multiple interconnected social graphs as used in this specification. Different social graphs can get generated for different types of connections a user has. For example, a user can get connected with chat contacts in one social graph, electronic message contacts in a second social graph, and connections (or contacts) from a particular social networking service in a third-social chart.

Each social graph can include edges to additional individuals or entities at higher degrees of separation from the user. These contacts can, in turn, have other contacts at another degree of separation from the user. Similarly, a user’s connection to someone in a particular social network can then get used to identifying additional connections based on that person’s connections. The distinct social graphs can include edges connecting social graphs to other social graphs.

Types of Connections And Social Graphs

Types of connections and social graphs can include, but are not limited to other searchers in which the searcher is:

• Direct contact (e.g., searcher mail or chat contact, direct contacts on social sites)
• Indirect contact (e.g., friends of friends, connections of searchers that have a direct connection to the searcher).
• The Content generated by individuals (e.g., blog posts, reviews).

The social graph can include connections within a single network or across multiple networks (separable or integrated). Public social graph relationships can also be considered. In some examples, public relationships can get established through public profiles and public social networking services.

Sources of the social graph information

The searcher’s social graph is a collection of connections (such as searchers, and resources) identified as having a relationship to the searcher within a specified degree of separation. The searcher’s social graph can include people and particular content at different degrees of separation.

For example, the social graph of a searcher can include:

• Friends,
• Friends of friends (e.g., as defined by a searcher, social graphing site, or another metric)
• The searcher’s social circle
• People followed by the searcher (such as subscribed blogs, feeds, or websites)
• Co-workers
• Fother specifically identified the content of interest to the searcher (e.g., particular websites)

The diagram shows a searcher and example connections that extend a searcher’s social graph to people and content both within a system and across external networks and shown at different degrees of separation. For example, a searcher can have a:

• Profile or contacts list that includes a set of identified friends
• Links to external resources (e.g., web pages)
• Subscriptions to the content of the system (e.g., a system that provides various content and applications including e-mail, chat, video, photo albums, feeds, or blogs)

Each of these groups can get connected to other searchers or resources at another degree of separation from the searcher. For example, the friends of the searcher each have their own profile that includes links to resources as well as friends of the respective friends.

The Social Graph Of The Searcher

Connections to a searcher within a specified number of degrees of separation can get considered in the social graph of the searcher. The number of degrees of separation used in determining the searcher’s social graph can get specified by the searcher. A default number of degrees of separation is used. Moreover, a dynamic number of degrees of separation can get used that is based on, for example, the type of connection.

The membership and degree of separation in the social graph are based on other factors, including the frequency of interaction. For example, a frequency of interaction by the searcher (e.g., how often the searcher visits a particular social graphing site) or type of interaction (e.g., endorsing or selecting items associated with friends). As interaction changes, the relationship of a particular contact in the social graph can also dynamically change. Thus, the social graph can get dynamic rather than static.

Social signals can get layered over the social graph (e.g., using weighted edges or other weights between connections in the social graph). These signals, for example, frequency of interaction or type of interaction between the searcher and a particular connection, can then get used to weight particular connections in the social graph or social graphs without modifying the actual social graph connections. These weights can change as the interaction with the searcher changes.

Social graphs can get stored using suitable data structures (e.g., list or matrix type data structures). Information describing any aspect of a stored social graph can get considered relationship data. For example, relationship data can include information describing how particular members of a searcher’s social graph are connected to the searcher (e.g., through what social path is a particular entity connected to the searcher).

Social Signals In the Social Graph

Relationship data can also include information describing any relevant social signals incorporated in the searcher’s social graph. Relationship data can get stored in a relationship lookup table (e.g., a hash table).

Suitable keys for locating values (e.g., relationship data) within the lookup table can include information describing the respective identities of both a searcher and any member of the searcher’s social graph. For example, a suitable key for locating relationship data within the lookup table can get (Searcher X, Searcher Y), where Searcher Y is a member of Searcher X’s social graph.

Using Social Graph Information

The system identifies a searcher. The searcher can get identified, for example, based on a searcher profile associated with the system. The searcher profile can get identified, for example, when the searcher logs in to the system using a searcher name, electronic message address, or another identifier.

The system finds the searcher’s social graph. The searcher’s social graph identifies people and resources associated with the searcher, for example, in which the searcher has indicated an interest. The social graph is limited to a specified number of degrees of separation from the searcher or particular relationships or types of interaction with the searcher.

The searcher’s social graph is generated by another system and provided upon request. In some examples, the searcher’s social graph can get provided as an index that identifies each member of the searcher’s social graph and indicates services, through which the searcher and the member are connected (e.g., electronic message contacts, social networking contacts, etc.).

The Searcher’s Social Graph Is Determined Using Searcher Profile Data

To look at Topicality scores, the searcher’s social graph is determined using searcher profile data, as well as extracting information from searchers and resources identified in the searcher profile data. For example, the searcher’s profile can include a list of the searcher’s friends. The searcher’s friends can include friends within the system (e.g., using the same e-mail or chat service that is affiliated with the system) or external to the system (e.g., social graphs or a list of contacts associated with third-party applications or services providers). The searcher’s profile can also include a list of subscriptions to which the searcher belongs (e.g., identifying content that the searcher follows, for example, particular blogs or feeds).

The searcher’s profile can also include external links identified by the searcher. These links can identify particular content of interest. The searcher’s profile also identifies other aliases used by the searcher (e.g., as associated with particular content providers or social graph sources).

A searcher may have a first identity for a chat application and a second identity for a restaurant review website. These two identities can get linked together in order to unify the content associated with that searcher.

The social graph can get further expanded by extracting information from the identified people and content in the searcher’s profile. For example, public profile information can exist for identified friends from which information can get extracted (e.g., their friends, links, and subscriptions). The searcher can adjust the members of the social graph directly. For example, the searcher can group their contacts (e.g., e-mail contacts) into particular groups accessed by the system in building the searcher’s social graph.

Similarly, a searcher can prevent the system from adding members to the searcher’s social graph, for example, by an opt-out option or by keeping contacts out of the particular groups used by the system to generate the social graph. Privacy features provide a searcher with an opt-in or opt-out option to allow or prevent, respectively, being included (or remove the searcher if already included) as a member of another’s social graph. Thus, searchers can have control over what personal information or connection information, if any, is included in social graphs.

The System Can Identify Information Associated With The Searcher’s Social Graph

The system can identify information associated with the searcher’s social graph. The identified information associated with the searcher’s social graph can include, for example, content or postings to web resources subscribed to by the searcher (e.g., particular blogs and microblogs). The identified information can also include content generated by members of the searcher’s social graph. For example, members of a searcher’s social graph can generate content including local reviews (e.g., for restaurants or services), video reviews and ratings, product reviews, book reviews, blog comments, news comments, maps, public web annotations, public documents, streaming updates, photos, and photo albums.

The system can index the identified information associated with the searcher’s social graph for use in information retrieval. Identified information associated with the searcher’s social graph can get indexed by generating and incorporating suitable data structures, such as social restrictions, in an existing search index.

The system can generate social restrictions by mapping the identified information to corresponding web resources referenced in a search index and determining the social connection between the web resources and the searcher. For example, the system can access a relationship lookup table which includes relationship data describing a searcher’s social graph to determine such social connections. In some examples, social restrictions can get provided in the form of an information tag associated with a referenced web resource included in the search index.

Retrieving and Presenting Search Results Including Social Graph Information

The search system receives a search query from a searcher. For example, the searcher can input a search query into a search interface of a particular system. The search query includes terms and can get general or directed to particular types of resources (e.g., a web search or an image search).

The searcher can submit the search query from a client device. The client can get a computer coupled to the search system through a local area network (LAN) or wide area network (WAN), e.g., the Internet. The search system and the client device are single machines. For example, a searcher can install a desktop search application on the client device. The searcher can submit the search query to a search engine within the search system.

When the searcher submits the search query, the search query is transmitted through a network to the search system. The search system can get implemented as, for example, computer programs running on computers in locations that are coupled to each other through a network.

Retrieving Search Results Relevant To The Received Query

The search system retrieves search results including search results associated with the searcher’s social graph. For example, the system can retrieve search results including content generated by members of the searcher’s social graph. The search system can include a search engine for retrieving search results relevant to the received query. The search engine can include:

• An indexing engine that indexes resources (e.g., web documents such as web pages, images, or news articles on the Internet) found in a corpus (e.g., a collection or repository of content)
• A search index that stores the index information
• A resource locator for identifying resources within the search index that are responsive to the query (for example, by implementing a query text matching routine)
• In some examples, the search engine can also include a ranking engine (or other software) to rank web resources that match the query

The indexing and ranking of the web resources can get performed using conventional or other techniques. The identified information associated with the searcher’s social graph can get included in the same index as other resources or a separate index. Consequently, a separate search can get performed for general search results responsive to the query, as well as particular search results that identify resources associated with the searcher’s social graph (e.g., endorsed web resources).

The system presents search results including search results associated with the searcher’s social graph. For example, the search system can present search results representing content generated by members of the searcher’s social graph and the searcher themself.

The search engine can transmit retrieved search results through the network to the client device for presentation to the searcher, for example, as search results on a web page to get displayed in a web browser running on the client device. The search system presents responsive search results associated with the searcher’s social graph together in a cluster, separate from any general search results. The system presents search results associated with the searcher’s social graph intermixed with any retrieved general search results.

SERPs That Includes Results Associated With The Searcher’s Social Graph

The search results page displays example search results responsive to the example query “safari in Tanzania.” In the depicted example, the displayed search results include web search results and image search results. The web search results include search results. The search results are associated with resources (e.g., web pages) that are publicly accessible on the Internet.

The search result includes searcher-generated content that is deemed to get relevant to the search query. In the example, the search result includes access-controlled content provided as a post that is distributed using a social networking service. For example, the author user “Jane Friend” generated the post and distributed the post to select searchers. In the depicted example, the distribution for the post is provided as “Limited,” indicating that only searchers selected by the author user are able to access the post.

Consequently, “Jane Friend” is a member of the searcher’s social graph and the searcher has been identified in the distribution. In some examples, the distribution can include a public distribution, such that any searcher, whether the contact of the author user, is able to access the post.

The image results include responsive search results associated with images that are publicly available and images that are associated with a social graph of the user. For example, the image results can include images. In the depicted example, the images can include publicly available images and the image includes an image that is posted by a member of the searcher’s social graph. For example, the image can get an image posted by the searcher “Jane Friend,” who authored the post provided as the search result.

Searcher-Generated Content In SERPs Based On A Searcher’s Social Graph

The example components include a search component, a content data source, a searcher-generated content data source, and a profile data source. In some examples, the search component can get provided as computer programs executed using computing devices (e.g., servers). In some examples, each of the data sources can get provided as computer-readable storage devices (e.g., databases).

The search component can communicate with each of the data sources via a network (e.g., a local area network (LAN) or wide area network (WAN), the Internet). The search component receives searcher input, processes the searcher input based on data of provided from the data sources, and generates search results. The searcher input can get provided via a computing device (e.g., a client computing device) and the search results can get provided to the computing device for display to the searcher.

The search component can identify a searcher profile based on the searcher input and can retrieve profile data corresponding to the searcher from the profile data source. In some examples, the searcher profile data can include a contact index. The contact index can get used to identifying members of the searcher’s social graph. For example, the searcher’s social graph can include the searcher’s U.sub.1, . . . U.sub.n.

The searcher input can include a search query that is received by the search component. In response to receiving the search query, the search component can process data provided by the content data source and the searcher-generated data source to generate search results. In some examples, in response to receiving the search query, the search component can retrieve the contact index 510 corresponding to the searcher that provided the search query (e.g., based on the searcher’s log-in information).

Accessing The Searcher-Generated Data Source

The search component can access the searcher-generated data source to retrieve searcher-generated content that may get relevant to the search results and that the search searcher is allowed access to. In some examples, the searcher-generated content can include electronic messages, chats, posts to social networking services, blog posts, and micro-blog posts.

The searcher-generated content can get content that is generated by members of the searcher’s social graph or content that is generated by the searcher themselves.

The search component can receive the searcher-generated content and data associated with the searcher-generated content. The search component can determine whether particular searcher-generated content is to get provided as search results. In some examples, and as discussed in further detail herein, the search component can determine whether and how to display particular searcher-generated content as search results based on the parameters. In some examples, whether the particular searcher-generated content is to get displayed can get determined based on the search query.

By way of non-limiting example, the searcher-generated content can include a post that is posted to a social networking service. Example data associated with the post can include a timestamp,  topicality scores (TS), and post scores (PS) (also referred to as an overall score).

The timestamp indicates the time that the post was distributed to the social networking service. In some examples, the timestamp indicates a time when an event occurred to the post. Example events can include a comment on the post, a re-sharing of the post, and an endorsement of the post.

The Topicality Score Indicates The Degree To Which The Content Pertains To The Search Query

Topicality scores can indicate the degree to which the content f the post pertains to the search query. In some examples, topicality scores can indicate the degree to which the content of the post pertains to a matter of interest. In some examples, content can pertain to a matter that is recently in the news.

For example, a matter of interest can include a natural disaster and can get a frequent topic of content distributed on the Internet within a given time period. If the content of the post relates to the natural disaster, the post may get deemed to get topical and can have associated topicality scores reflecting this.

The Post Score and Topicality Scores

In some examples, the post score (or overall score) reflects the quality of the post and the relevance of the post to the particular searcher. For example, the post can have a first post score associated therewith that reflects the quality of the post and the relevance of the post to a first searcher. The post can have a second post score associated therewith that reflects the quality of the post and the relevance of the post to a second searcher. The first post score and the second post score can get different from one another.

The topicality scores and the post scores are generated by a scoring service and can get provided to the searcher-generated content data store.

Whether the searcher-generated content is to get displayed in the search results can get determined based on the search query. It can get determined whether the search query provided by the searcher is a trending search query.

A Trending Search Query

A trending search query can include a search query that is frequently provided to a searching service for a given period of time. By way of non-limiting example, a first search query can get provided to the searching service X times by various searchers within the last Y days. A second search query can get provided to the searching service Z times by various searchers within the last Y days. A first frequency can get determined based on X and a second frequency can get determined based on Z.

The first frequency and the second frequency can get compared to a threshold frequency. If a frequency is greater than or equal to the threshold frequency, the associated search query can get deemed to get a trending search query. For example, the first frequency is greater than or equal to the threshold frequency and the second frequency is less than the threshold frequency. Consequently, the first search query is determined to get a trending search query, and the second search query is not determined to get a trending search query.

Searcher-generated content can get identified as a potential search result based on the relevance of the searcher-generated content to the search query. In some examples, if the identified searcher-generated content is determined to get sufficiently recent and is determined to get sufficiently topical, the searcher-generated content is displayed as a search result.

If the searcher-generated content is not deemed to get sufficiently recent or the searcher-generated content is not deemed to get sufficiently topical, it can get determined whether the search query used to identify the searcher-generated content as a potential search result is a trending query. If the search query is a trending query if the searcher-generated content is deemed to et somewhat recent and if the searcher-generated content is determined to get somewhat topical, the searcher-generated content is displayed as a search result.

If The Search Query Is Not A Trending Query

If the query is not a trending query, if the searcher-generated content is not deemed to get somewhat recent or if the searcher-generated content is not determined to get somewhat topical, and, if the post score of the searcher-generated content is greater than or equal to a threshold post score, the searcher-generated content is displayed as a search result.

If the search query is not a trending query, if the searcher-generated content is not deemed to get somewhat recent or if the searcher-generated content is not determined to get somewhat topical, and if the post score of the searcher-generated content is less than a threshold post score, the searcher-generated content is not displayed as a search result.

In some examples, whether searchser-generated content is sufficiently recent can get determined based on a current time (t.sub.CURR), the timestamp of the searcher-generated content (t.sub.POST), and a first threshold (t.sub.THR1).

The current time is provided as the time at which the search query is submitted by the searcher In some examples, a time difference (t.sub.DIFF) can get determined as a difference between the current time and the timestamp of the searcher-generated content. If the time difference is less than the first threshold, the searcher-generated content can get determined to get sufficiently recent.

Whether searcher-generated content is somewhat recent can get determined based on the current time, the timestamp of the searcher-generated content, and a second threshold (t.sub.THR2). In some examples, if the time difference is less than the second threshold, the searcher-generated content can get determined to get somewhat recent. In some examples, the first threshold is less than the second threshold.

Whether Searcher-Generated Content Has Sufficient Topicality Scores

Whether searcher-generated content is sufficiently topical can get determined based on a topicality score of the searcher-generated content (TS.sub.POST) and a first topicality score threshold (TS.sub.THR1). If the topicality score of the searcher-generated content is less than the first topicality score threshold, the searcher-generated content can gete determined to get sufficiently topical.

Whether searcher-generated content is somewhat topical can get determined based on topicality scores of the searcher-generated content and a second topicality score threshold (TS.sub.THR2). If the topicality scores of the searcher-generated content are less than the second topicality score threshold, the searcher-generated content can get determined to get somewhat topical. In some examples, the first topicality score threshold is greater than the second topicality score threshold.

If it is determined that the searcher-generated content is to get displayed in the search results, how and where the searcher-generated content is displayed can get determined. In some examples, the searcher-generated content can get displayed at the bottom of a search results page. In some examples, the searcher-generated content can get displayed within other search results (e.g., in the middle of a search results page).

By way of non-limiting example, if the time difference, discussed above, is less than a third threshold (t.sub.THR3) and the topicality score is greater than or equal to a third threshold topicality score (TS.sub.THR3), the searcher-generated content is provided within other search results (e.g., in the middle or towards the top of a search results page).

The first threshold is equal to the third threshold. In some examples, the topicality scores threshold is equal to the third topicality score threshold. It can get determined that the searcher-generated content of the search result is associated with a time difference that is less than the third threshold and topicality scores that are greater than or equal to the third threshold topicality scores.

Consequently, the Searcher-generated content of the search result is displayed in line with the other search results.

Searcher-Generated Content That Includes An Image

Searcher-generated content that includes an image can get analyzed to determine where to display the searcher-generated content within the search results. If the searcher-generated content includes a single image and text, the searcher-generated content can get displayed as a web search result. If the searcher-generated content includes images without text, the image can get displayed within the image search results.

The image can get an image that was provided in a post that was distributed using a social networking service and that did not include text. Consequently, the image is displayed in the image search results instead of the underlying post getting displayed as a search result in and of itself. If the searcher-generated content includes a plurality of images with text, the searcher-generated content can get displayed as a web search result web the images can get displayed as image search results.

An Account With The Searcher’s Confidential Or Non-Public Searcher-Generated Content

A searcher may provide permission (e.g., to a search engine) to access an account containing the searcher’s confidential or non-public searcher-generated content. The searcher may give a search engine permission to access an electronic messaging account, a calendar, a cloud drive, and so forth. The search engine may:

• Index messages or other content in the account
• Retrieve messages or other content that match a search query
• Present these messages, or portions thereof, in search results

If an input search query does not specifically request electronic messaging content (e.g., if the query were to read “biking in Tahoe” only), the search engine may still make confidential or non-public search content available to the searcher. A search query (e.g., “biking in Tahoe”), does not include the option to identify the type of searcher-generated content that it contains. For example, the option can specify electronic messages.

Additional options may get is available to provide relevant content, e.g., from a searcher’s online calendar, cloud drive, and so forth.

Selecting a corresponding option displays the corresponding content. For example, selecting the option to view electronic messages may cause the display of portions of electronic messages. Selecting a displayed electronic message may direct the searcher to their messaging account to view the entire contents of that message. The same may get true for other types of content, such as calendar content and cloud drive documents.

Processes Involving Topicality Scores From The Present

For convenience, the topicality scores process will get described using a system including computing devices that performs the process.

• The ID of the searcher is determined
• And the ID of the searcher can get determined based on searcher log-in information (e.g., searcher name and password)
• A contact index corresponding to the searcher ID is retrieved
• A search query is received
• Whether the search query is a trending search query
• If the search query is a trending search query, a trending search query indicator is set

Whether Search Results Include Searcher-Generated Content

Search results are generated and are received. It is determined whether the search results include searcher-generated content. In the example context, it is determined whether the search results include digital content (e.g., posts) distributed by contacts of the searcher within a computer-implemented social networking service. If the search results do not include searcher-generated content, the search results are displayed.

If the SERPs include searcher-generated content, it is determined whether the searcher-generated content is to get displayed in the search results. In the example context, it is determined whether digital content (e.g., posts) distributed by contacts of the searcher within the computer-implemented social networking service is to get displayed.

If the searcher-generated content is not to get displayed, the searcher-generated content is removed from the search results and the search results are displayed. If it is determined that the searcher-generated content is to get displayed, the searcher-generated content is blended with the other search results and the search results are displayed.

About Bill Slawski

With more than 26 years of SEO experience and a Juris Doctor Degree, Bill Slawski is the foremost expert on Google’s patents as related to SEO. Patent Exploration is one of the quickest and most detailed ways to find new information about SEO. Bill is the Editor of SEO by the Sea, a prominent search engine optimization blog, where he is the author of over 1,300 posts. Bill’s experience includes Fortune 500 brands and some of the largest websites in the world. Bill is a contributing author for Moz, Search Engine Land, and Search Engine Journal. In 2014-2021, he spoke at industry-leading international conferences about topics including search engine algorithms, universal and blended search, personalization in search, search and social, and duplicate content problems, structured data, and schema