Abstract: Due to the noisy nature of global positioning systems (GPS), tracing a signal from a device of a delivery provider may be inadequate for the task of determining a best dispatch time. However, leveraging motion data from mobile devices provides a more detailed picture of when a delivery provider is on the road, walking, or waiting. Using this data, an example embodiment creates a trip state model that enables segmenting out each stage of a trip. The trip state model enables collection and use of historical data for individual restaurants, which allows a dispatch system to optimize pickup and delivery times for both delivery providers and consumers.

Abstract: Techniques for leveraging a social graph to facilitate the delivery of relevant recommendations. For example, a recommender is identified based on the recommender being a member of a social networking service who has interacted with an item of web-based content. A recommendee is identified based on the recommendee being another member of the social networking service who is connected to the recommender via a social graph maintained by the social networking service and based on having an affinity score for the item that exceeds a recommendee affinity score threshold and a connection strength to the recommender that exceeds a connection strength threshold. The recommender is sent a communication that invites the recommender to recommend the item to the recommendee. With some example embodiments, the communication is sent to the recommender within a pre-determined time measured from the time the recommender initiated an interaction with the item of web-based content.

Abstract: This disclosure relates to systems and methods that include receiving media content from a content submitter, classifying the media content by initiating one of synchronous classification and asynchronous classification based on a type of the media content, generating a media content certificate based on the media type, the certificate including results of the classification, storing the media content certificate with the media content, and filtering the media content based on at least one of an identity of the content submitter, the results of the classification, and the media content including malicious content.

Abstract: This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.

Abstract: Systems and methods are disclosed for determining whether a short amount of text is irrelevant. Initially, an article is selected having one or more comments of varying length. Depending on the number of comments available, a native context may be constructed based on a given comment and other neighboring comments. In other embodiments, a transferred context may be constructed from the given comment and topically similar comments extracted from other, topically similar articles. A native context-aware feature may be determined from the constructed native context and a transferred context-aware feature may be determined from the constructed transferred context. These features may be leveraged by a language classifier to determine whether a given comment is irrelevant.

Abstract: This disclosure relates to systems and methods that include receiving media content from a content submitter, classifying the media content by initiating one of synchronous classification and asynchronous classification based on a type of the media content, generating a media content certificate based on the media type, the certificate including results of the classification, storing the media content certificate with the media content, and filtering the media content based on at least one of an identity of the content submitter, the results of the classification, and the media content including malicious content.

Abstract: This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.

Abstract: The disclosed systems and methods are directed to detecting spam in an electronic presentation and determining whether the electronic presentation should be moderated. The example systems and methods may employ one or more classifiers for classifying an electronic presentation and, should the electronic presentation fall within a predetermined classification, the electronic presentation may be analyzed further for the presence of spam. Further analysis of the electronic presentation may include invoking one or more filters to determine whether the electronic presentation includes words and/or phrases known to be associated with spam. Where the electronic presentation is determined to contain spam, the electronic presentation may be removed from a database of electronic presentations, excluded from search results, or flagged for moderation by a moderator.

Abstract: Systems and methods are disclosed for determining whether a short amount of text is irrelevant. Initially, an article is selected having one or more comments of varying length. Depending on the number of comments available, a native context may be constructed based on a given comment and other neighboring comments. In other embodiments, a transferred context may be constructed from the given comment and topically similar comments extracted from other, topically similar articles. A native context-aware feature may be determined from the constructed native context and a transferred context-aware feature may be determined from the constructed transferred context. These features may be leveraged by a language classifier to determine whether a given comment is irrelevant.

Abstract: Techniques for leveraging a social graph to identify senders and recipients of relevant recommendations and to facilitate the delivery of the relevant recommendations from the senders to the recipients are described. For example, a recommender is identified based on the recommender being a member of a social networking service who has interacted with an item of web-based content. A recommendee is identified based on the recommendee being another member of the social networking service who is connected to the recommender via a social graph maintained by the social networking service and based on having an affinity score for the item that exceeds a recommendee affinity score threshold and a connection strength to the recommender that exceeds a connection strength threshold. The recommender is sent a communication that invites the recommender to recommend the item to the recommendee.