Abstract: In some implementations, a computing device can present a multi-language grouping of topics. For example, the computing device can determine a primary and secondary language for a user of the computing device. The computing device can request configuration that includes a tag language mapping that can be used to translate topic tags corresponding to the secondary language to topic tags corresponding to the primary language. When the computing device receives tagged content items associated with the secondary language, the computing device can translate the secondary language tags corresponding to the tagged content items into semantically equivalent topic tags in the primary language. The computing device can then group primary language content items and secondary language content items into multi-language groupings based on the topics corresponding to the translated content item tags. The computing device can then present the multi-language topic groupings of content items.

Abstract: In some implementations, a computing system can deliver personalized content while preserving user privacy. For example, the computing system can include a content server that filters and selects aggregate content items (e.g., magazine issues, newspaper issues, etc.) that are relevant to a subject matter tag (e.g., investment identifier) received in a request from a client device. The content server can send the selected aggregate content items to the requesting client. Upon receiving the aggregate content items, requesting client device can evaluate and select aggregate content items to present to the user based on user preferences stored on the user device. The selected aggregate content items can then be presented on a display of the user device. Thus, personalization of aggregate content item selection and presentation can be performed without distributing user preference data outside of the user device thereby preserving user privacy.

Abstract: In some implementations, a computing device can present a multi-language grouping of topics. For example, the computing device can determine a primary and secondary language for a user of the computing device. The computing device can request configuration that includes a tag language mapping that can be used to translate topic tags corresponding to the secondary language to topic tags corresponding to the primary language. When the computing device receives tagged content items associated with the secondary language, the computing device can translate the secondary language tags corresponding to the tagged content items into semantically equivalent topic tags in the primary language. The computing device can then group primary language content items and secondary language content items into multi-language groupings based on the topics corresponding to the translated content item tags. The computing device can then present the multi-language topic groupings of content items.

Abstract: Aspects of the present disclosure involve a mobile or computer reader application that obtains articles or other computer files from a central database and displays the articles to a user of the device. In addition to providing the articles to the reader application, an article providing system may also determine the quality or popularity of particular articles and provide the most popular articles to users of the system. In one embodiment, the system may receive one or more anonymous interaction metrics from one or more devices connected to the system. The anonymous interaction metrics may be associated with a particular article and provide some indication of a user's engagement with the article. The system utilizes these interaction metrics or measurements to set or adjust a score or ranking associated with the particular article.

Abstract: Aspects of the present disclosure may involve a computer implemented method of disambiguating a string from an article involving an electronic device including one or more hardware processing units, and accessing a disambiguation database comprising a plurality of string-entity combinations and associated metrics for each of the plurality of string-entity combinations. The associated metrics may include a metric associated with an arrival probability of linking at a web page for a particular entity after a specified number of links from a starting page. The method may involve generating a clique graph for each candidate entity of the article, and generating a probability that a particular candidate entity matches a particular string associated with the particular candidate entity as a function of score attributes generated from the clique graph and the arrival probability of linking at the page for the particular entity after the specified number of links.

Abstract: Aspects of the present disclosure involve a mobile or computer reader application that obtains articles or other computer files from a central database and displays the articles to a user of the device. The reader application may be customizable around one or more characteristics of the user of the device. In one embodiment, the type and number of articles provided to the device and displayed in the reader application may be based on the determination of a category or type of usage of the application is performed by the user. Further, the determination of the use of the reader application on the device is performed by and contained within the device such that usage information is not shared with overall article providing system. In another embodiment, the article providing system and/or device may determine recommendations to provide to a user of the reading application. These recommendations may be based on one or more selected interests or topics of the user of the reading application.

Abstract: Aspects of the present disclosure involve a mobile or computer reader application that obtains articles or other computer files from a central database and displays the articles to a user of the device. The reader application may be customizable around one or more characteristics of the user of the device. In one embodiment, the type and number of articles provided to the device and displayed in the reader application may be based on the determination of a category or type of usage of the application is performed by the user. Further, the determination of the use of the reader application on the device is performed by and contained within the device such that usage information is not shared with overall article providing system. In another embodiment, the article providing system and/or device may determine recommendations to provide to a user of the reading application. These recommendations may be based on one or more selected interests or topics of the user of the reading application.

Abstract: Aspects of the present disclosure involve a mobile or computer reader application that obtains articles or other computer files from a central database and displays the articles to a user of the device. The reader application may be customizable around one or more characteristics of the user of the device. In one embodiment, the type and number of articles provided to the device and displayed in the reader application may be based on the determination of a category or type of usage of the application is performed by the user. Further, the determination of the use of the reader application on the device is performed by and contained within the device such that usage information is not shared with overall article providing system. In another embodiment, the article providing system and/or device may determine recommendations to provide to a user of the reading application. These recommendations may be based on one or more selected interests or topics of the user of the reading application.

Abstract: Aspects of the present disclosure involve a mobile or computer reader application that obtains articles or other computer files from a central database and displays the articles to a user of the device. In addition to providing the articles to the reader application, an article providing system may also determine the quality or popularity of particular articles and provide the most popular articles to users of the system. In one embodiment, the system may receive one or more anonymous interaction metrics from one or more devices connected to the system. The anonymous interaction metrics may be associated with a particular article and provide some indication of a user's engagement with the article. The system utilizes these interaction metrics or measurements to set or adjust a score or ranking associated with the particular article.