Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: One or more techniques and/or systems are provided for displaying related content associated with browsing a website. For example, a user may access a website to view content provided by the website. As opposed to the user manually searching for interesting content through trial and error, related content that may be interesting to the user may be identified and surfaced to the user. For example, a user profile specifying user interests of the user may be used to identify related content assigned topics corresponding to the user interests (e.g., content provided by the website or other web source). In this way, the related content may be displayed to the user through a content recommendation reader interface. In an example, the content recommendation reader interface may be provided by a web browser so that related content may be identified and/or provided to users of any website from any device.

Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: One or more techniques and/or systems are provided for displaying related content associated with browsing a website. For example, a user may access a website to view content provided by the website. As opposed to the user manually searching for interesting content through trial and error, related content that may be interesting to the user may be identified and surfaced to the user. For example, a user profile specifying user interests of the user may be used to identify related content assigned topics corresponding to the user interests (e.g., content provided by the website or other web source). In this way, the related content may be displayed to the user through a content recommendation reader interface. In an example, the content recommendation reader interface may be provided by a web browser so that related content may be identified and/or provided to users of any website from any device.

Abstract: In one implementation, a computer-implemented method for determining user interests includes receiving user activity data that describes an interaction between a user and digital content. The method further includes generating first interest-level data that quantifies a first level of interest between the user and an entity that is a topic of the digital content, where the entity is of a plurality of entities included within a knowledge base. The knowledge base includes an ontology that indicates relationships between the plurality of entities. The method further includes identifying a candidate entity based on the candidate entity having one of the relationships to the entity within the knowledge base. Additionally, the method includes generating second interest-level data that quantifies a second level of interest between the user and the candidate entity based on an analysis of the one of the relationships of the candidate entity to the entity within the knowledge base.

Abstract: One or more techniques and/or systems are provided for displaying related content associated with browsing a website. For example, a user may access a website to view content provided by the website. As opposed to the user manually searching for interesting content through trial and error, related content that may be interesting to the user may be identified and surfaced to the user. For example, a user profile specifying user interests of the user may be used to identify related content assigned topics corresponding to the user interests (e.g., content provided by the website or other web source). In this way, the related content may be displayed to the user through a content recommendation reader interface. In an example, the content recommendation reader interface may be provided by a web browser so that related content may be identified and/or provided to users of any website from any device.

Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: In one implementation, a computer-implemented method for determining user interests includes receiving user activity data that describes an interaction between a user and digital content. The method further includes generating first interest-level data that quantifies a first level of interest between the user and an entity that is a topic of the digital content, where the entity is of a plurality of entities included within a knowledge base. The knowledge base includes an ontology that indicates relationships between the plurality of entities. The method further includes identifying a candidate entity based on the candidate entity having one of the relationships to the entity within the knowledge base. Additionally, the method includes generating second interest-level data that quantifies a second level of interest between the user and the candidate entity based on an analysis of the one of the relationships of the candidate entity to the entity within the knowledge base.

Abstract: One or more techniques and/or systems are provided for displaying related content associated with browsing a website. For example, a user may access a website to view content provided by the website. As opposed to the user manually searching for interesting content through trial and error, related content that may be interesting to the user may be identified and surfaced to the user. For example, a user profile specifying user interests of the user may be used to identify related content assigned topics corresponding to the user interests (e.g., content provided by the website or other web source). In this way, the related content may be displayed to the user through a content recommendation reader interface. In an example, the content recommendation reader interface may be provided by a web browser so that related content may be identified and/or provided to users of any website from any device.

Abstract: Content pre-render and pre-fetch techniques are described. In one or more implementations, a likelihood is predicted of subsequent navigation to content associated with a network address based at least in part on monitored navigation performed by a computing device to one or more network addresses. A determination is then made whether to cause the computing device to pre-fetch and pre-render the content based at least in part on the prediction.

Abstract: Described is a paid search advertising technology in which advertisements associated with bidding keywords are ranked by relevance when returning one or more advertisements in a response to a query. A relevance score is computed for an advertisement based on the bidding keyword and page data (text and/or other page content) of the advertisement. The relevance score may be based on a similarity vector score computed from a keyword vector and page data vector relationship, combined with a proximity score computed from the keyword's bigram set and the page data bigram set. When a query is received, advertisements are selected based on the proximity of the query to each advertisement's bidding keyword, providing candidate scores. Each candidate score is modified (e.g., multiplied) into a final score based on its respective advertisement's relevance score. The final scores are then used to re-rank the advertisements relative to one another.

Abstract: Described is a paid search advertising technology in which advertisements associated with bidding keywords are ranked by relevance when returning one or more advertisements in a response to a query. A relevance score is computed for an advertisement based on the bidding keyword and page data (text and/or other page content) of the advertisement. The relevance score may be based on a similarity vector score computed from a keyword vector and page data vector relationship, combined with a proximity score computed from the keyword's bigram set and the page data bigram set. When a query is received, advertisements are selected based on the proximity of the query to each advertisement's bidding keyword, providing candidate scores. Each candidate score is modified (e.g., multiplied) into a final score based on its respective advertisement's relevance score. The final scores are then used to re-rank the advertisements relative to one another.