Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a ranking machine learning model. In one aspect, a method includes the actions of receiving training data for a ranking machine learning model, the training data including training examples, and each training example including data identifying: a search query, result documents from a result list for the search query, and a result document that was selected by a user from the result list, receiving position data for each training example in the training data, the position data identifying a respective position of the selected result document in the result list for the search query in the training example; determining, for each training example in the training data, a respective selection bias value; and determining a respective importance value for each training example from the selection bias value for the training example, the importance value.

Abstract: Methods and apparatus related to using document feature(s) of a document that is responsive to a query, and optionally query feature(s) of the query, to determine a presentation characteristic for presenting a search result that corresponds to the document. In some implementations, measures associated with the document feature(s) and/or query feature(s) may be used to determine the presentation characteristic. The measures may be based on past interactions, by corresponding users, with other documents that share one or more of the document features with the document, where a plurality of the other documents are different from the document (and optionally each different from one another). In some implementations, the document and/or the other documents include, or are restricted to, documents that are access restricted.

Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.

Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.

Abstract: Methods and apparatus related to using document feature(s) of a document that is responsive to a query, and optionally query feature(s) of the query, to determine a presentation characteristic for presenting a search result that corresponds to the document. In some implementations, measures associated with the document feature(s) and/or query feature(s) may be used to determine the presentation characteristic. The measures may be based on past interactions, by corresponding users, with other documents that share one or more of the document features with the document, where a plurality of the other documents are different from the document (and optionally each different from one another). In some implementations, the document and/or the other documents include, or are restricted to, documents that are access restricted.

Abstract: Methods and apparatus related to using document feature(s) of a document that is responsive to a query, and optionally query feature(s) of the query, to determine a presentation characteristic for presenting a search result that corresponds to the document. In some implementations, measures associated with the document feature(s) and/or query feature(s) may be used to determine the presentation characteristic. The measures may be based on past interactions, by corresponding users, with other documents that share one or more of the document features with the document, where a plurality of the other documents are different from the document (and optionally each different from one another). In some implementations, the document and/or the other documents include, or are restricted to, documents that are access restricted.

Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate identification of additional trigger-terms for a structured information card. In one aspect, the method includes actions of accessing data associated with a template for presenting structured information, wherein the accessed data references (i) a label term and (ii) a value. Other actions may include obtaining a candidate label term, identifying one or more entities that are associated with the label term, identifying one or more of the entities that are associated with the candidate label term, and for each particular entity of the one or more entities that are associated with the candidate label term, associating, with the candidate label term, (i) a label term that is associated with the particular entity, and (ii) the value associated with the label term.

Abstract: Methods and apparatus related to using document feature(s) of a document that is responsive to a query, and optionally query feature(s) of the query, to determine a presentation characteristic for presenting a search result that corresponds to the document. In some implementations, measures associated with the document feature(s) and/or query feature(s) may be used to determine the presentation characteristic. The measures may be based on past interactions, by corresponding users, with other documents that share one or more of the document features with the document, where a plurality of the other documents are different from the document (and optionally each different from one another). In some implementations, the document and/or the other documents include, or are restricted to, documents that are access restricted.

Abstract: In various implementations, a plurality of non-private n-grams that satisfy a privacy criterion may be identified within a search log of private search queries and corresponding post-search activity. A plurality of query patterns may be generated based on the plurality of non-private n-grams. Aggregate search activity statistics associated with each of the plurality of query patterns may be determined from the search log. Aggregate search activity statistics associated with each query pattern may be indicative of search activity associated with a plurality of private search queries in the search log that match the query pattern. In response to a determination that aggregate search activity statistics for a given query pattern satisfy a performance criterion, a methodology for generating data that is presented in response to search queries that match the given query pattern may be altered based on aggregate search activity statistics associated with the given query pattern.

Abstract: In various implementations, a plurality of non-private n-grams that satisfy a privacy criterion may be identified within a search log of private search queries and corresponding post-search activity. A plurality of query patterns may be generated based on the plurality of non-private n-grams. Aggregate search activity statistics associated with each of the plurality of query patterns may be determined from the search log. Aggregate search activity statistics associated with each query pattern may be indicative of search activity associated with a plurality of private search queries in the search log that match the query pattern. In response to a determination that aggregate search activity statistics for a given query pattern satisfy a performance criterion, a methodology for generating data that is presented in response to search queries that match the given query pattern may be altered based on aggregate search activity statistics associated with the given query pattern.

Abstract: An optimization-based framework is utilized to extract broad query aspects from query reformulations performed by users in historical user session logs. Objective functions are optimized to yield query aspects. At run-time, the best broad but unspecified query aspects relevant to any user query are presented along with the results of the run time query.

Abstract: An optimization-based framework is utilized to extract broad query aspects from query reformulations performed by users in historical user session logs. Objective functions are optimized to yield query aspects. At run-time, the best broad but unspecified query aspects relevant to any user query are presented along with the results of the run time query.

Abstract: A human or hand-labeled ranking of URL results for a search query is compared against actual click data for the respective query/URL pairs (e.g., which URLs were actually clicked on by users when the URLs were presented to users when the search query was run in the real world). The human ranking or ordering of the URL results (e.g., pre-existing relevance ranking) for the query can then be adjusted, if necessary, based upon the real world click data (e.g., click relevance ranking). The modified pre-existing relevance ranking can be used in providing future search results.

Abstract: Methods, systems, and computer programs are presented for providing internet content, such as related news articles. One method includes an operation for defining a plurality of candidates based on a seed. For each candidate, scores are calculated for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on a relevance score of the intersection between the words in the seed and the words in each of the candidates. Further, the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate. For each candidate, a relatedness score is calculated based on the calculated scores for relevance, novelty, connection clarity, and transition smoothness. In addition, at least one of the candidates is selected based on their relatedness scores for presentation to the user.

Abstract: Methods, systems, and computer programs are presented for providing internet content, such as related news articles. One method includes an operation for defining a plurality of candidates based on a seed. For each candidate, scores are calculated for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on a relevance score of the intersection between the words in the seed and the words in each of the candidates. Further, the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate. For each candidate, a relatedness score is calculated based on the calculated scores for relevance, novelty, connection clarity, and transition smoothness. In addition, at least one of the candidates is selected based on their relatedness scores for presentation to the user.

Abstract: A human or hand-labeled ranking of URL results for a search query is compared against actual click data for the respective query/URL pairs (e.g., which URLs were actually clicked on by users when the URLs were presented to users when the search query was run in the real world). The human ranking or ordering of the URL results (e.g., pre-existing relevance ranking) for the query can then be adjusted, if necessary, based upon the real world click data (e.g., click relevance ranking). The modified pre-existing relevance ranking can be used in providing future search results.

Abstract: A human or hand-labeled ranking of URL results for a search query is compared against actual click data for the respective query/URL pairs (e.g., which URLs were actually clicked on by users when the URLs were presented to users when the search query was run in the real world). The human ranking or ordering of the URL results (e.g., pre-existing relevance ranking) for the query can then be adjusted, if necessary, based upon the real world click data (e.g., click relevance ranking). The modified pre-existing relevance ranking can be used in providing future search results.

Abstract: A human or hand-labeled ranking of URL results for a search query is compared against actual click data for the respective query/URL pairs (e.g., which URLs were actually clicked on by users when the URLs were presented to users when the search query was run in the real world). The human ranking or ordering of the URL results (e.g., pre-existing relevance ranking) for the query can then be adjusted, if necessary, based upon the real world click data (e.g., click relevance ranking). The modified pre-existing relevance ranking can be used in providing future search results.

Abstract: Systems and methods for searching heterogeneous interrelated entities for a heterogeneous entities search query are disclosed herein. A user may enter the heterogeneous entities search query. The search retrieves and returns multiple types of heterogeneous entities. The retrieved heterogeneous interrelated entities are searched in a unified matrix that represents relationships between one or more heterogeneous entities. The retrieved heterogeneous interrelated entities may have one or more entity types. The set of retrieved interrelated entities may also be ranked based on the similarity between each entity and the search query. Feedback may also be incorporated into the system to improve search accuracy.