Abstract: The disclosed systems and methods provide a framework for a proactive prediction of the toxic propensity of an article. Prior to the publication and/or reception of comments to online content, the disclosed framework determines the toxic propensity of the content's context and/or specific words, sentences, sentiments, tone or other messages receivable from consumption of the content. Thus, disclosed framework performs proactive forecasting of the content's toxicity propensity”, which quantifies how likely the content is prone to incur or attract toxic comments. The framework can function and/or be configured to operate in a manner that can perform specifically adherent moderation actions that correspond to the content and control how the content can be interacted with, based on the toxic propensity determination, prior to the content's publication in an effort to thwart, prevent or stop toxic environments surrounding or stemming from the content from coming into existence.

Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for predicting user actions of provided digital content based on an aggregation of user data. Conventional user tracking, and action prediction and recommendation systems have a lifespan that is ending in the short term due to new privacy laws. The disclosed framework enables personalized recommendations to be formulated for specific users based on an imputation from user data aggregated from a plurality of users. While anonymity is maintained, recommendations for predicted actions can be provided to the users and/or the providers of the content. The disclosed framework can scale the aggregated user data using a Naïve Bayes classifier, from which a logistic regression modeling can be performed to determine the predicted recommendation.

Abstract: Systems, devices, and methods are disclosed for predicting potential effectiveness of query-triggered internet advertisements received from different web page publishers using a deep learning neural network language model for clustering queries, and for automatically adjusting bids for advertisements by advertisers based on the predicted potential effectiveness. Using query-clusters rather than queries for adjusting bids for advertisements allows for more accurate and more consistent bidding strategy despite of sparsity in historical advertisement performance data, higher return on investments for the advertisers, and higher revenue for the publishers of the advertisements.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: A system and method enable exploration of cold ads in an online information system. Cold ads are ads that are new to the system and do not yet have reliable click through rate (CTR) estimates or click probabilities. The method and system selectively boost the click probabilities of cold ads to increase their likelihood of participating in and winning an auction so that the cold ad get more impressions, but without adversely affecting revenue in a production environment when cold ads are introduced.

Abstract: Systems, devices, and methods are disclosed for predicting potential effectiveness of query-triggered internet advertisements received from different web page publishers using a deep learning neural network language model for clustering queries, and for automatically adjusting bids for advertisements by advertisers based on the predicted potential effectiveness. Using query-clusters rather than queries for adjusting bids for advertisements allows for more accurate and more consistent bidding strategy despite of sparsity in historical advertisement performance data, higher return on investments for the advertisers, and higher revenue for the publishers of the advertisements.

Abstract: A system and method enable exploration of cold ads in an online information system. Cold ads are ads that are new to the system and do not yet have reliable click through rate (CTR) estimates or click probabilities. The method and system selectively boost the click probabilities of cold ads to increase their likelihood of participating in and winning an auction so that the cold ad get more impressions, but without adversely affecting revenue in a production environment when cold ads are introduced.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: A server accesses an initial query associated with a classification, the classification corresponding to a likely intent of the initial query. The server obtains a set of queries, wherein each query in the set of queries is identified as having resulted in one or more users selecting a resource that was selected by one or more users in response to submitting the initial query. The server then determines a metric for one or more queries in the set of queries, wherein the metric for each of the one or more queries in the set of queries is based on a similarity between the respective query and the initial query. Next, the server selects a subset of queries from the set of queries based on the metric for each selected query satisfying a threshold and associates the selected subset of queries with the classification of the initial query.

Abstract: The present teaching relates to methods, systems, and programming for providing advertisements based on semantic representations. In one example, a request is obtained for advertisement. The request incorporates a query. The query is parsed to generate a semantic representation of the query. A plurality of advertisements indexed by their respective semantic representations is obtained. Among the plurality of advertisements, one or more advertisements are determined whose semantic representations match the semantic representation of the query. The one or more advertisements are provided as a response to the request.

Abstract: In some implementations, data that indicates multiple candidate transcriptions for an utterance is received. For each of the candidate transcriptions, data relating to use of the candidate transcription as a search query is received, a score that is based on the received data is provided to a trained classifier, and a classifier output for the candidate transcription is received. One or more of the candidate transcriptions may be selected based on the classifier outputs.

Abstract: Methods, systems, and computer programs are presented for unified recognition of speech and music. One method includes an operation for starting an audio recognition mode by a computing device while receiving an audio stream. Segments of the audio stream are analyzed as the audio stream is received, where the analysis includes simultaneous checking for speech and music. Further, the method includes an operation for determining a first confidence score for speech and a second confidence score for music. As the audio stream is received, additional segments are analyzed until the end of the audio stream or until the first and second confidence scores indicate that the audio stream has been identified as speech or music. Further, results are presented on a display based on the identification of the audio stream, including text entered if the audio stream was speech or song information if the audio stream was music.

Abstract: In some implementations, data that indicates multiple candidate transcriptions for an utterance is received. For each of the candidate transcriptions, data relating to use of the candidate transcription as a search query is received, a score that is based on the received data is provided to a trained classifier, and a classifier output for the candidate transcription is received. One or more of the candidate transcriptions may be selected based on the classifier outputs.

Abstract: Subject matter described pertains to methods, devices, and servers for transmitting and responding to a location declaration.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: Content recommendations customized to a user's knowledge are provided. The user's knowledge is assessed from the user's activity history and the expertise of the user regarding each of the various topics relative to a cohort group is determined. Based on the user's score, the user can be classified into various competency levels ranging from a novice to an expert in each topic. Content items for improving the user's scores in the various topics can be forwarded based on the user's classification and activity history. If the user is recognized as an expert in a particular topic, questions from other users regarding the particular topic can be directed to the user for the responses.

Abstract: News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.

Abstract: Subject matter described pertains to methods, devices, and servers for transmitting and responding to a location declaration.