Using pre-search triggers

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using pre-search triggers. In one aspect, a method includes identifying one or more topics and determining that a confidence score associated with a particular topic of the one or more identified topics satisfies a predetermined threshold value. An occurrence of a pre-search trigger can be detected. In response to determining that the confidence score associated with the particular topic satisfies the predetermined threshold value and detecting the occurrence of the pre-search trigger, a search engine can be instructed to execute a search using a search query associated with the particular topic. A representation of a resource identified in results received in response to the search can be provided.

BACKGROUND

The present specification relates to information retrieval.

Internet search engines identify resources (e.g., web pages, images, text documents, multimedia content) that are relevant to a user's information needs, and present information about the resources in a manner that is useful to the user. Typically, users submit queries that suggest the information the users want to retrieve, and search engines provide search results that are responsive to the queries.

SUMMARY

A search engine system can perform a search and can provide information to a user before the user submits a search query, for example in response to detecting a pre-search trigger. The search engine system predicts a topic likely to be of interest to the user. When the search engine system detects a pre-search trigger and determines that a confidence score for the predicted topic is above a threshold, the search engine identifies a resource related to the topic by causing a search to be performed. The search engine system then provides a representation of the identified resource to the user.

One innovative aspect of the subject matter described in this specification is embodied in methods that include the actions of: identifying one or more topics; determining that a confidence score associated with a particular topic of the one or more identified topics satisfies a predetermined threshold value; detecting an occurrence of a pre-search trigger; instructing a search engine to execute a search using a search query associated with the particular topic in response to (i) determining that the confidence score associated with the particular topic satisfies the predetermined threshold value, and (ii) detecting the occurrence of the pre-search trigger; and providing a representation of a resource identified in results received in response to the search.

These and other embodiments may each optionally include one or more of the following features. For instance, the pre-search trigger occurs before the user enters a query term. Detecting the occurrence of the pre-search trigger includes receiving information indicating that a control on a user interface of a client device has been selected. Detecting the occurrence of the pre-search trigger includes receiving a request to provide a resource. Providing a representation of the resource includes causing navigation to be redirected to the selected resource. Providing a representation of the resource includes providing a resource that, when rendered, causes content of the selected resource to be displayed on a portion of a user interface. Providing a representation of the resource includes providing a resource including a link to the selected resource. The confidence score is based on a browsing history of a user or a search query history of a user. The identifying, determining, detecting, instructing, and providing are performed by a server system. The identifying, determining, detecting, instructing, and providing are performed by a client computing device. Identifying one or more topics includes selecting a topic from a predetermined set of topics. Identifying one or more topics includes generating a topic based on based on a browsing history of a user or a search query history of a user.

Advantageous implementations can include one or more of the following features. A user can receive information by performing few or no actions. Information can be provided to a user in response to a pre-search trigger. Information can be provided to a user before a search query is submitted. Delays in providing information to a computing device can be avoided. Predicted content can provided quickly to a computing device.

DETAILED DESCRIPTION

FIG. 1is a diagram of an example of a system100that can provide information in response to a pre-search trigger. The system100includes a client device102, a server system104, and a network106. The client device102can be, for example, a desktop computer, laptop computer, cellular phone, smart phone, tablet computer, a music player, an e-book reader, or navigation system. The functions performed by the server system104can be performed by individual computer systems or can be distributed across multiple computer systems.

A search engine system can enhance a user's experience by providing information about a topic of interest to the user before the user initiates a search or enters a search query. The search engine system identifies a topic, for example, “movies,” “baseball,” or “fishing in Colorado.” Using information about a particular user, the search engine system generates a confidence score indicating a likelihood that the identified topic will be of interest to the particular user. The search engine system predicts that the topic is likely of interest to the user when the confidence score satisfies a threshold. The search engine system may identify multiple topics, and can simultaneously provide content for multiple topics satisfying the threshold or provide content for a topic assigned the highest confidence score.

A user can access a search engine interface, for example, by navigating to a web page providing an interface to the search engine. Data indicating this access to the search engine interface is a pre-search trigger, which is detected by the search engine system. The search engine determines that the pre-search trigger is associated with the user. In response to the pre-search trigger, the search engine system performs a search to select a resource associated with the topic predicted to be of interest to the user. The search engine system then provides a representation of the selected resource to the user.

For example, the search engine can provide search results that include a link to a web page that, when rendered, causes content of the selected resource to be displayed, or causes a link to the selected resource to be displayed. Because the selected resource is identified based on the predicted topic rather than a search query entered by the user, information related to the topic can be provided to the user before the user enters a search query. When the server system does not identify a topic having a confidence score above the threshold, a representation of a resource selected based on a predicted topic is not provided. A representation of a resource can include, for example, a link, a snippet, a summary, an excerpt, a portion of an interface, a snapshot, and so on. In some implementations, the form of the representation can be determined based on the confidence score or other signals used to assign the confidence score.

The server system104can include a topic prediction module120, a confidence score evaluation module130, a topic-to-resource mapping module140, and a page generation module150, described in further detail below. The network110can be wired or wireless or a combination of both and can include the Internet. The diagram shows states (A) to (G), which may occur in the sequence illustrated or in a different sequence. States (A) to (C) and (E) to (G) illustrate a flow of data, and states (D) and (H) illustrate user interfaces150a,150b.

During state (A), the server system104identifies one or more topics. The identified topics can be a general set of topics or topics that are predicted to be of interest to a particular user101. For each identified topic, the server system104generates a confidence score indicating a likelihood that the corresponding topic is of interest to the user101at the current time.

In the illustrated example, the topic prediction module120identifies a topic121, “surfing.” The topic prediction module120also generates a confidence score122of 95%, which indicates a predicted likelihood that the user101would be interested in viewing or receiving content related to the topic121. As used herein, content is defined broadly to include an interactive interface, for example, an e-mail interface or on-line banking interface. Thus a user's interest can include an interest in performing a particular action through an interactive interface, in addition to consuming media or receiving non-interactive information.

Topics can be categories of information, whether broad or narrow, for example, “sports,” “bagpipes,” “kayaking,” etc. Topics can be selected from a predefined set of topics or can be dynamically generated by the server system104. A topic can include multiple components, for example, “kayaking in California.” Examples of topics also include a search query composed of one or more terms, a category of web pages, or a particular resource. Topics can be search queries submitted by the user101or by other users.

The topic prediction module120of the server system104can identify topics from a collection of predefined topics or can generate new topics. The topic prediction module120can use information about the user101to identify topics. The information can include, for example, demographic information, location information, an Internet browsing history, and a search query history of the user101. For example, the topic prediction module120can compose a topic using keywords and other aspects of a browsing history or search history of the user101. The topic prediction module can also select topics based on the device type of the client device102, applications on the client device102, the location of the user or the client device102, user-defined indicated topics or topics expressly indicated by the user101, social connections, and external factors. These signals, described in further detail below, can be used to identify topics and to generate confidence scores for identified topics.

The topic prediction module120can identify topics based on a device type of the client device102, for example, whether the client device102is a smartphone, tablet computer, laptop computer, or desktop computer. The topic prediction module120can infer a range of likely information needs of the user101based on the device type, and thus filter the topics likely to be of interest to the user101.

In a similar manner, the topic prediction module120can also access information about applications installed on or currently running on the client device102. The topic prediction module120can identify applications on the client device102and access a database indicating topics associated with the identified applications. The topic prediction module120can consider topics associated with an identified application to be more likely to be of interest to the user101.

The topic prediction module120can also use the location of the client device102to infer likely information needs of the user101and to select corresponding topics. To identify a location or type of location where the client device102is located, the topic prediction module120can compare the current location of the client device102with known locations of significance to the user, for example, a home location, a workplace location, and frequently visited locations, or with standard maps or location databases. If the client device102is determined to be located at the workplace of the user101, for example, topics related to office productivity and the profession of the user101, if known, can be selected. By contrast, topics related to entertainment can be selected if the client device102is determined to be located at the user's home. If the client device102is determined to be located on a road, the topic prediction module120can select topics related to maps, navigational directions, or local attractions. In a similar manner, appropriate topics can be selected if the client device102is determined to be located at a school, theater, beach, or other location.

Topics can also be selected based on a user's social connections. For example, the topic prediction module120can access information about the user's social connections from, for example, a social networking service, an e-mail contacts list, an employment web page, or other sources. Topics that are indicated to be of interest to the social connections of the user101can be selected, as they are also likely to be of interest to the user101.

Additionally, external factors such as environmental conditions, such as the weather, temperature, season of the year, and time of day can be used to select topics. For example, outdoor activities may be more likely to be of interest when sunny rather than raining, in summer rather than winter, and during the day rather than at night. The physical or environmental context of the client device102can be used to select topics. For example, if the client device102is determined to be docked in a vehicle, the location of refueling stations may be selected as a topic of interest, especially if data is available indicating that the vehicle is determined to be low on fuel. The topic prediction module120can identify other events or conditions, such as news releases or stock price movements, that may cause a topic to become of interest to the user101.

Information about the user101, such as an Internet browsing history and search query history, can be associated with an identifier125for the user101, such as a user account for the user101or a cookie stored on the client device102of the user101. The topic prediction module120can identify topics that the user101is likely to be interested in, for example, topics related to or corresponding to previous search queries of the user101.

The topic prediction module120uses information about the user101and the client device102to generate confidence scores for the identified topics. The topic prediction module120can use any of the information used to select a topic to generate a confidence score. The confidence score for each topic is generated based on, for example, the degree that the topic matches information about the user101. The higher the correlation between a topic and information about the user101, the higher the confidence score for the topic.

The confidence score122can represent a level of interest in the topic121corresponding to a particular time. Even though the user101may always have a general interest in the topic121, the user101may be likely to view or request information about the topic at particular times. Thus the confidence score122for a topic121can be time-dependent, indicating that the interest of the user101in receiving information about the topic121is a function of time. At different times through the day, and from one day to another, the value of the confidence score122for the topic121changes for the user101, even when the information about the user101does not change. For a given time, the confidence score122for the topic121can indicate a degree of correlation between the topic and actions of the user101at similar times. Information about the user101can indicate patterns of behavior of the user101, which the topic prediction module120can use to generate time-dependent confidence scores.

As an example, information about the user101can indicate that the user101usually searches for information about surfing in the morning on weekends. A curve123illustrates an example relationship between the confidence score122and the topic121over the course of a day. The curve123is illustrated as an example, and the topic prediction module120need not generate confidence scores for any range of time or generate confidence scores as a continuous function. The curve123indicates that the topic is highly correlated with actions of the user101during mornings, and less correlated with actions of the user101during afternoons. A point124on the curve123represents the confidence score122of 95% for the topic121at the current time.

During state (B), the server system104determines whether the confidence score for each of the one or more identified topics satisfies a threshold. For example, the confidence score evaluation module130determines that the confidence score122of 95% exceeds a minimum threshold of 90%. This indicates that there is a high likelihood that the user101is interested in viewing content related to the topic121at the current time. In some implementations, the confidence score evaluation module130determines whether each confidence scores satisfies one or more of multiple thresholds, which can each represent a different level of interest. Topics that satisfy at least one threshold can be made accessible to the topic-to-resource module130.

To reduce the likelihood of presenting information that is not useful to a user, the server system104can use a high minimum threshold, for example, a minimum threshold of about 70% or higher. Using a high minimum threshold can also conserve network bandwidth by avoiding transfer of information not useful to a user. When a user has browsed or searched for information about a topic irregularly or infrequently, a low confidence score, for example, 40%, may be generated. The low confidence score indicates significant uncertainty that the user will find information about the topic to be useful at a particular time. By contrast, when the user has regularly and frequently requested information about a topic, or otherwise accesses information about the topic with a predictable pattern, a high confidence score, for example, 80%, can be generated. The high confidence score indicates that, for a particular time, the user is very likely to find information about the topic useful.

In some implementations, the server system104uses a user-specific confidence threshold for each user. The server system104can adjust the threshold for a particular user based on the behavior of the user. For example, the server system104can set a high confidence threshold for a user with a browsing history indicating a narrow or consistent range of topics. The server system104can set a lower threshold for a user that browses web pages associated with many topics, or if a browsing history indicates that topics of interest change frequently. Users having similar browsing patterns can be assigned similar confidence thresholds.

In addition, the confidence threshold can be adjusted based on the user's interaction with content provided by the server system104. For example, the server system104may determine that a user sometimes clicks on content presented by the server system104when the confidence score for an associated topic is above a particular value, for example, 70%, but that the user does not click on content associated with topics assigned lower confidence scores. As a result, the server system104may set the confidence threshold for the user at 70%, corresponding to the minimum confidence level eliciting any user interaction. The server system104can alternatively set the confidence threshold at a level corresponding to a particular level or frequency of user interaction.

In some implementations, the server system104repeats states (A) and (B). Over time, the server system104can periodically predict topics that, for the current time or a particular time range, have confidence scores exceeding a threshold. Thus before receiving a request to execute a search, the server system104can have already identified topics the user101is currently likely to be interested in. In the same manner that topics of interest are identified for the user101, the server system104can also identify topics predicted to be of interest to other users.

During state (C), using the client device102, the user101performs an action that generates a pre-search trigger. A predetermined set of actions or conditions can be designated as suggestive of a user's intent to initiate a search. The pre-search trigger can be data that indicates that an action or condition in the set has occurred. For example, the pre-search trigger can be data that indicates a user action to initiate a dialogue with a search engine. Examples of such actions include initiating navigation to a web page for a search engine, causing a search toolbar to be displayed, or speaking a voice command signaling that a search will follow. As another example, the user101can select a control for receiving a query term, for example, by clicking in a text field in which query terms can be entered. Data indicating any of these actions can be a pre-search trigger, which can be detected in state (D) below.

In the illustrated example, the user101initiates navigation to a web page for a search engine. The user interface150adisplays the user interface for a web browser, including an address bar107for receiving a URL. The user101initiates navigation to a search engine web page114, accessible at the URL “www.example.com/SEARCH.” The user101selects a control108on the user interface150aand the client device102transmits a request110, for example, an HTTP request or SPDY request, to retrieve the web page114. The request includes an identifier112or other information identifying the user101. The identifier112can be, for example, a username of a user account or information stored in a cookie on the client device102.

In some implementations, the client device102also transmits to the server system104a request to retrieve a resource in response to actions other than initiating navigation. For example, in response to a mouse click in a text field for receiving a query term, the client device102can transmit information indicating that the mouse click occurred. The information can be a request to retrieve a resource, and the request can indicate that a search is predicted to occur, even when no text is entered in the field.

In some implementations, different pre-search triggers can be defined for different types of client devices. For example, for a phone, a pre-search trigger can be data indicating an acceleration level that indicates that a user has picked up the phone. For a tablet computer, the pre-search trigger can be data indicating that the user touched a touchscreen, or data indicating that the tablet computer has recently emerged from a low-power state. Other examples of pre-search triggers can include, for example, data indicating that a browser has been launched and data indicating that a cursor of a pointing device is approaching a search toolbar or a desktop icon for a search engine. Data indicating that a user is approaching the client device102, for example, sound from a microphone or video from a camera, can also be a pre-search trigger.

During state (D), the server system104detects the pre-search trigger and identifies the user101associated with the pre-search trigger. In the example, the server system104receives the request110and identifies the request110as a pre-search trigger. The server system104also determines that the pre-search trigger is associated with the user101, for example, by determining that the identifier112matches the identifier125.

As described above, a pre-search trigger is data indicating that one or more actions or conditions in a predetermined set have occurred. The predetermined set of actions or conditions can include actions or conditions that enable a user to initiate a dialogue with a search engine. The pre-search trigger can thus indicate that a search is likely to be subsequently requested, before a search is actually requested. Nevertheless, a pre-search trigger does not require a subsequent search request or subsequent input of query terms. For example, after navigating to the web page114, the user101may navigate to a different page without actually entering or submitting a search query.

A pre-search trigger can indicate a state in which a user can immediately enter a query term, for example, the placement of a text cursor in a query-receiving field. As another example, a pre-search trigger can indicate a state in which a user can enter a query term after performing a single action, such as selecting a control that is displayed on a user interface or will be rendered after a resource is received. A pre-search trigger can indicate an action of the user101to access to a search interface, for example: initiating navigation to a resource that, when rendered, provides a search interface; causing a search toolbar or search interface to be displayed; and clicking on a text field for receiving a query term.

The pre-search trigger can occur before query terms for a search are entered, selected, or otherwise specified. Thus the pre-search trigger can occur before any query term for the search—even a single character—is received by the server system104or is entered on the client device102.

To detect the pre-search trigger, the server system104can receive data from the client device102or access data from another source, such as another server system. The pre-search trigger can be, for example, a request to provide a resource, a notification of an event, or information indicating a state of the client device102. To determine whether accessed data includes a pre-search trigger, the server system104can determine whether the accessed data indicates one or more of a set of predetermined actions or conditions enabling a user to initiate a dialogue with a search engine system.

During state (E), the server system104selects a resource related to the topic121predicted to be of interest to the user101. The topic121is predicted to be of interest to the user101at the time of the pre-search trigger. For example, confidence score122can correspond to substantially the same time as the request110, or can fall within a range of time, e.g., five minutes or one hour, from the time of the request110. Because the confidence score122for the topic121satisfies the threshold, and because the pre-search trigger is detected, the server system104selects a resource related to the topic121. If multiple topics have confidence scores that satisfy the threshold, the server system104can select a resource related to each of the multiple topics.

To select a resource, the topic-to-resource mapping module140can, for example, instruct a search engine to execute a search using a search query associated with the topic121. The topic-to-resource mapping module140can access a stored query for the topic121or can generate a query for a topic121. The topic-to-resource mapping module140can select a resource identified in results to the search returned by the search engine. A topic can indicate a particular media type, and the topic-to-resource mapping module140can cause the search engine to return results corresponding to resources of the indicated media type, for example, web page, image, video, or music. In some implementations, to select a resource for a topic, the topic-to-resource mapping module140can select a resource having a predetermined mapping to a particular topic.

In the example, the request110for the search engine web page114indicates that, at the current time, the user101likely intends to search for and view as-yet unspecified information. Because the user101has not entered any query terms for a search, the particular topic for which the user101desires to retrieve content cannot be discerned from the request110.

Nevertheless, by periodically predicting topics of interest to the user101, the server system104has identified a topic121that is likely to be of interest to the user101at the current time. For the topic121, the topic-to-resource mapping module140causes a search to be performed with a query term “surfing.” From results received in response to the search, the topic-to-resource mapping module140selects the resource corresponding to the top-ranking result, a resource141accessible at Uniform Resource Locator (URL) of “www.example.com/SURF.”

During state (F), the server system102generates information to provide to the client device102. The server system104can generate a search result or search results page that includes a representation of the resource141.

In the example, the page generator module150generates a resource151that, when rendered on the client device102, causes a search engine web page and a link to the resource141to be displayed. The resource151is thus customized for the user101so that, when rendered, content related to the topic121is displayed. The page generator module150can access content of a resource141from a cache142to provide the content to the user101with a minimal delay.

A representation of a resource can include one or more of, for example, a link to a resource, a portion of content of the resource, or the entire resource. A representation of a resource can include code that causes the resource to be retrieved and rendered, for example, in an inline frame (“iFrame”) or other display area. In some implementations, a representation of the resource141can be provided by causing navigation to be redirected to the resource141.

In some implementations, the server system104selects the representation of the resource141based on the confidence score122. For example, the server system104can select a different representation for the resource141when the confidence score122satisfies different thresholds. For example, if the confidence score122exceeds a high threshold, the resource141can be displayed in a search engine web page, for example, in an iFrame or through any other manner of displaying content within a web page. If the confidence score122exceeds a low threshold but not the high threshold, a link to the resource141can be provided.

If the server system104does not identify a topic having a confidence score that satisfies the threshold, then no representation of a resource is provided. The page generator module150can respond to the pre-search trigger by providing a search engine web page, without topical customization. For some pre-search triggers, such as selection of a text field for entering a query, the server system104can ignore the pre-search trigger when no topic has a confidence score determined to satisfy a threshold.

During state (G), the server system104transmits the resource151to the client device102in response to the request110.

As an alternative, as described below, one or more actions illustrated as performed by the server system104can be performed by the client device102. In such implementations, the client device102need not receive a resource from the server system104. For example, the client device102may generate a user interface that includes a link to the resource141.

During state (H), the client device102displays the rendered resource151on the user interface160b. The user interface160bdisplays a search engine interface including, for example, a control161for receiving a query term. The user interface160balso displays a link162to the resource141.

Through the link to the resource141, the user101can quickly access the resource141and gain information about the topic121. The user101can select the link162to navigate directly to the resource141, whereas the user101would traditionally select the control161, enter a search query, select a control to submit the search query, receive a search engine results page, and select a link for the resource141from a search engine results page. In addition to, or as an alternative to, display of a link162, content of the resource141can be provided immediately with the search engine interface. Thus the user101can quickly access information related to the topic121.

Additionally, information is not provided for topics that are not determined to have confidence scores satisfying the threshold. As a result, the search interface is supplemented with additional information for topics determined to be of interest to the user, and information related to topics not determined to be of interest to the user is excluded.

In some implementations, the actions described for states (A) to (H) can be performed in a different sequence, for example, as illustrated inFIG. 4. As another example, selecting a resource related to a topic, as described for state (E), can be performed before detecting a pre-search trigger. Thus when the server system104detects the pre-search trigger in state (D), the server system104can previously have selected a resource141corresponding to the topic121, permitting the server system104to quickly provide a representation of the resource121to the user in response to detecting the pre-search trigger.

In some implementations, the actions described for states (A) to (H) can be performed by the client device102, for example, by downloaded code or by a browser or other application running on the client device102. For example, the client device102can identify one or more topics, generate or access confidence scores for the identified topics, and determine whether the confidence scores satisfy one or more thresholds. When a topic is determined to satisfy a threshold, the client device102can select a corresponding resource and display a representation of the resource.

FIG. 2is a flow chart illustrating an example of a process200for providing information in response to a pre-search trigger. Briefly, the process200includes identifying one or more topics, determining that a confidence score associated with a particular topic of the one or more identified topics satisfies a predetermined threshold value, and detecting an occurrence of a pre-search trigger. The process200also includes instructing a search engine to execute a search using a search query associated with the particular topic in response to (i) determining that the confidence score associated with the particular topic satisfies the predetermined threshold value, and (ii) detecting the occurrence of the pre-search trigger, and providing a representation of a resource identified in results received in response to the search.

One or more topics are identified (202). The topics can be selected from a predefined hierarchy of topics. The topics can be identified based on information about a particular user based on a browsing history of the user and a search query history of the user.

A confidence score associated with a particular topic of the one or more identified topics is determined to satisfy a predetermined threshold value (204). The confidence score can be determined for the particular user based on a browsing history of the user and a search query history of the user. The confidence score can indicate a degree of correlation between the particular topic and actions of the user.

When confidence scores for multiple topics satisfy the predetermined threshold value, the topic with the highest confidence score can be selected. As an alternative, the N topics with the highest confidence scores can be selected, where N is a predetermined integer. In some implementations, each topic that has a confidence score that satisfies the threshold can be selected. As described below, for each topic selected, a corresponding resource can be identified, and a representation of the identified resources can be provided in response to detecting a pre-search trigger.

An occurrence of a pre-search trigger is determined (206). The pre-search trigger can be determined to be associated with the particular user for which the confidence score is determined to satisfy the threshold value. The pre-search trigger can be an action to initiate a dialogue with a search engine. For example, the pre-search trigger can be data indicating an action to gain access to a search engine interface, such as an interface or control for receiving a query term. The pre-search trigger can occur during a browsing session before a query term is entered.

Detecting the occurrence of the pre-search trigger can include receiving information indicating that a control on a user interface of a client device has been selected. Detecting the occurrence of the pre-search trigger can include receiving a request to provide a resource that provides a search interface.

A search engine is instructed to execute a search using a search query associated with the particular topic (208). The search is executed in response to (i) determining that the confidence score associated with the particular topic satisfies the predetermined threshold value and (ii) detecting the occurrence of the pre-search trigger.

A representation of a resource identified in results received in response to the search is provided (210). The resource can be a resource referenced by the top-ranking result of the results received in response to the search. The representation of the resource can be provided such that it is displayed with a search engine interface.

Providing a representation of the resource can include causing navigation to be redirected to the resource. Providing a representation of the resource can include providing a resource that, when rendered, causes content of the selected resource to be displayed on a portion of a user interface, for example, in a frame or an iFrame of a search engine web page. Providing a representation of the resource can include providing a resource including a link to the selected resource.

FIG. 3Ais an example of a user interface300that illustrates a search engine home page that includes a representation of a resource. The search engine home page includes three images302a-302cthat represent different resources, which correspond to topics that are predicted to be of interest to the user. Multiple topics can be selected when each of the multiple topics has a confidence score that satisfies an appropriate threshold. If many topics have confidence scores that satisfy the threshold, a predetermined number of topics having the highest confidence scores, for example, the topics assigned the top three confidence scores, can be selected. In response to a pre-search trigger, a representation of a resource corresponding to each selected topic can be displayed.

The user interface300displays a search interface301and the images302a-302c. The images302a-302crepresent three different resources, each corresponding to one of three different topics, “surf report,” “e-mail,” and “finance.” The images302a-302cdisplayed can be rendered from image files referenced by each resource, for example, images that would be displayed if the corresponding resource were rendered. Alternatively, the images302a-302ccan be “snapshot” images displaying a rendered representation of a portion of or all of the respective resources. As another alternative, the images302a-302ccan each be icons or symbols representing the respective resources or the topics corresponding to the resources.

In some implementations, multiple alternatives can be presented to the user to provide a sense of choice. For example, when a representation of an associated resource is presented, representations of other resources for the same topic or representations of resources associated with different topics can also be presented. Representations of alternative resources can be presented as links, snippets, layers, lists, images, icons, and so on. For example, when a server system can predict a product of interest and a user's preferred retailer, representations of resources offering the product can be provided, both from the preferred retailer and other retailers. The information about alternative retailers can provide welcome choices to the user and may allay suspicions that the prediction algorithm is attempting to sway the user's behavior.

FIG. 3Bis an example of a user interface330that illustrates a search engine home page that includes a representation of a resource. The user interface330displays a search engine interface331and a rendering332of a resource that corresponds to a predicted topic for the user. After a pre-search trigger is detected, a web page can be provided that causes portions of or all of a resource corresponding to a predicted topic to be rendered. Content of a resource can be presented in an iFrame, or can be displayed in any other manner of displaying content in a web page. The rendering332can be displayed at, for example, the side, top, bottom, or other location of the user interface330.

The content of the rendering332can include one or more types of media, for example, a web page, a video, an audio recording, an image, an animation, or an embedded application. In some implementations, a server system selects the resource for a particular type of media based on information about the user. For example, if the user searched for images during the previous browsing session, the resource provided can be an image.

FIG. 3Cis an example of a user interface360that illustrates a search engine home page that includes a representation of a resource. A resource rendered by a client device can cause navigation to be redirected to a different resource, for example, a resource corresponding to a topic predicted to be of interest to the user. When a user navigates to the search engine home page, for example, the server system providing the search engine home page can detect a pre-search trigger. The search engine home page provided to the user can redirect navigation to a resource that corresponds to a topic predicted to be of interest to the user.

In the example, the search engine home page is rendered at a client device, causing a search interface361and a redirection notice362to be displayed. The search engine home page is personalized for the user and causes navigation to “www.example.com/SURF”, which corresponds to the topic predicted to be of interest to the user. The redirection notice362indicates that redirection will occur in a particular period of time, for example, in five seconds. As an alternative to delayed redirection, a search engine home page or other received resource can cause the user's browser to immediately navigate to the resource that corresponds to the predicted topic.

As another example, information about a user can indicate that, on weekdays between 9:00 am and 10:00 am, the user frequently enters a search for a particular e-mail web page. Using this information, a server system can identify the particular e-mail web page as a topic of interest for this range of time, and determine that a confidence score for the topic satisfies a threshold. When the user navigates to the search engine web page on a weekday between 9:00 am and 10:00 am, the server system can detect a request for the search engine web page as a pre-search trigger. In response, the server system can provide a resource that, when rendered, redirects the user's web browser to the e-mail site. As a result, the user receives access to the content of the e-mail site without entering a search query and reviewing search results.

In some implementations, a server system selects the type of representation to provide based on the confidence score for a topic predicted to be of interest to the user. For example, various ranges of confidence can correspond to, from highest confidence to lowest confidence, the server system: (i) causing immediate navigation to the selected resource; (ii) causing navigation to the selected resource after a time delay; (iii) providing a resource which causes content of the selected resource to be displayed; (iv) and providing a resource including a link to the selected resource. The confidence ranges for the presentation modes can respectively be, for example: (i) 90% and higher; (ii) 80% to 90%; (iii) 70% to 80%; and (iv) 60% to 70%. The higher the confidence score for the topic, the greater degree of content of the selected resource is provided.

In some implementations, a resource can be selected to provide an appropriate level of information based on the confidence score for the topic. For example, a topic may be purchasing a dishwashing machine from a particular retailer. If the confidence score for the topic is high, the resource selected can be a web page from the retailer providing details of a particular product for sale. If the confidence score is medium, the resource selected can be a web page for the kitchen appliances department of the retailer. If the confidence score is low, the resource selected can be the main page for the retailer.

In some implementations, the server system104selects the type of representation to provide based on the confidence score for a topic predicted to be of interest to the user. The higher the confidence score for the topic, for example, the greater degree of content of the selected resource is provided. For example, various ranges of confidence scores can correspond to, from highest confidence to lowest confidence, the server system104providing a resource: (i) causing immediate navigation to the selected resource; (ii) causing navigation to the selected resource after a time delay; (iii) providing content of the selected resource to be displayed, for example, with a search engine interface; and (iv) providing a link to the selected resource.

FIG. 4is a swim lane diagram illustrating an alternative sequence for a process400for providing information in response to a pre-search trigger. By contrast with the sequence ofFIG. 1, the process400includes generating a confidence score and determining whether the confidence score satisfies a threshold after detecting the pre-search trigger rather than before.

In the process400, the server system identifies a topic (406), for example predicting a topic likely to be of interest to a user at a particular time based on behavior patterns of the user. The server system can update predictions as new information about the behavior of the user is received, and can predict topics regardless of whether the user is currently in communication with the server system. For example, the server system can predict topics for a user even when the user has not yet initiated a search session or has logged in to a user account.

The client device transmits information indicating a pre-search trigger has occurred (404), and the server system detects a pre-search trigger (406). In response to the pre-search trigger, the server system generates a confidence score (408), and determines whether the confidence score satisfies a threshold (410). In the process400, the server system select a resource corresponding to topic (412), provides a representation of the selected resource to the client device (414), and the representation of the selected resource is received by the client device (416).

A number of variations can be implemented. For example, the server system can also generate the confidence score (408) and/or select a resource corresponding to topic (412) before detecting the pre-search trigger (406). As another example, the server system can generate the confidence score (408), determine whether the confidence score satisfies a threshold (410), and select a resource corresponding to topic (412) before detecting the pre-search trigger (406).

In some implementations, some or all of the actions of the process400described as performed by the server system can alternatively be performed by the client device. For example, an application running on the client device can directly detect a pre-search trigger, for example, by receiving user input, receiving information about system events, or by monitoring conditions or properties of the client device. The client device can also receive data indicating that the pre-search trigger occurs from another system. The client device can predict a topic or request a predicted topic from a server system, can generate a confidence score or request a confidence score from a server system, and can determine whether the confidence score satisfies a threshold. The client device can also select a resource corresponding to the topic by instructing a search engine of a server system to perform a search, or by instructing a local search engine to perform a search, for example, a search of a media collection or file system accessible to the client device. The client device can also generate a user interface that includes a representation of the selected resource rather than receiving a representation of a resource.

In each instance where a hypertext markup language (HTML) file is mentioned, other file types or formats may be substituted. For instance, an HTML file may be replaced by an extensible markup language (XML), JavaScript object notation (JSON), plain text, or other types of files. Moreover, where a table or hash table is mentioned, other data structures (such as spreadsheets, relational databases, or structured files) may be used.

Particular embodiments have been described. Other embodiments are within the scope of the following claims. For example, the steps recited in the claims can be performed in a different order and still achieve desirable results.