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: Implementations relate to training a model that can be used to process values for defined features, where the values are specific to a user account, to generate a predicted user measure that reflects both popularity and quality of the user account. The model is trained based on losses that are each generated as a function of both a corresponding generated popularity measure and a corresponding generated quality measure of a corresponding training instance. Accordingly, the model can be trained to generate, based on values for a given user account, a single measure that reflects both quality and popularity of the given user account. Implementations are additionally or alternatively directed to utilizing such predicted user measures to restrict provisioning of content items that are from user accounts having respective predicted user measures that fail to satisfy a threshold.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a tuple of respective input sequences to generate an output. In one aspect, one of the systems includes a neural network comprising a plurality of encoder neural networks and a head neural network, each encoder neural network configured to: receive a respective input sequence from the tuple; process the respective input sequence using one or more encoder network layers to generate an encoded representation comprising a sequence of tokens; and process each of some or all of the tokens in the sequence of tokens using a projection layer to generate a lower-dimensional representation, and the head neural network configured to: receive lower-dimensional representations of a respective proper subset of the sequence of tokens generated by the encoder neural network; and process the lower-dimensional representations to generate the output.

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, apparatus, and computer-readable media are provided for analyzing a cluster of communications, such as B2C emails, to generate a template for the cluster that defines transient segments and fixed segments of the cluster of communications. More particularly, methods, apparatus, and computer-readable media are provided for generating and/or applying a trained structured machine learning model for a generated template that can be used to determine, for one or more transient segments of subsequent communications, a corresponding probability that a given semantic label is the correct semantic label for extracted content of the transient segment(s).

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: Evaluating content includes receiving content, analyzing the content for web spam using a content-based identification technique, and classifying the content according to the analysis. An index of analyzed contents may be created. A system for evaluating content includes a storage device configured to store data and a processor configured to analyze content for web spam using content-based identification techniques.

Abstract: Different URLs that actually reference the same web page or other web resource are detected and that information is used to only download one instance of a web page or web resource from a web site. All web pages or web resources downloaded from a web server are compared to identify which are substantially identical. Once identical web pages or web resources with different URLs are found, the different URLs are then analyzed to identify what portions of the URL are essential for identifying a particular web page or web resource, and what portions are irrelevant. Once this has been done for each set of substantially identical web pages or web resources (also referred to as an “equivalence class” herein), these per-equivalence-class rules are generalized to trans-equivalence-class rules.

Abstract: Fault tolerance is provided for a database of hyperlinks distributed across multiple machines, such as a scalable hyperlink store. The fault tolerance enables the distributed database to continue operating, with brief interruptions, even when some of the machines in the cluster have failed. A primary database is provided for normal operation, and a secondary database is provided for operation in the presence of failures.

Abstract: The present invention provides for the efficient downloading of data set addresses from among a plurality of host computers, using a plurality of web crawlers. Each web crawler identifies URL's in data sets downloaded by that web crawler, and identifies the host computer identifier within each such URL. The host computer identifier for each URL is mapped to the web crawler identifier of one of the web crawlers. If the URL is mapped to the web crawler identifier of a different web crawler, the URL is sent to that web crawler for processing, and otherwise the URL is processed by the web crawler that identified the URL. Each web crawler sends URL's to the other web crawlers for processing, and each web crawler receives URL's from the other web crawlers for processing. In a preferred embodiment, each web crawler processes only the URL's assigned to it, which are the URL's whose host identifier is mapped to the web crawler identifier for that web crawler.

Abstract: A web crawler stores fixed length representations of document addresses in a buffer and a disk file, and optionally in a cache. When the web crawler downloads a document from a host computer, it identifies URL's (document addresses) in the downloaded document. Each identified URL is converted into a fixed size numerical representation. The numerical representation may optionally be systematically compared to the contents of a cache containing web sites which are likely to be found during the web crawl, for example previously visited web sites. The numerical representation is then systematically compared to numerical representations in the buffer, which stores numerical representations of recently-identified URL's. If the representation is not found in the buffer, it is stored in the buffer. When the buffer is full, it is ordered and then merged with numerical representations stored, in order, in the disk file.

Abstract: A system generates a list of near-uniform samples of data sets (e.g., web pages) from among a plurality of host computers. The system performs a random walk so as to generate a set of visited addresses. For each address in the set, a reachability measure is computed. Then, samples are selected from the set, such that the probability of selecting a given address is inversely proportional to the reachability measure for the address. The selected samples form the list of near-uniform samples.