Abstract: Techniques for automatic intelligent information extraction from an electronic document are disclosed. In one embodiment, a computerized method is disclosed comprising training a label prediction model to generate a set of label predictions, obtaining an electronic document, analyzing the electronic document and determining a set of features for each of a set of information items identified in the electronic document, obtaining model output from the label prediction model for each information item, the model output comprising, for a respective information item, a set of probabilities corresponding to a set of information classes, and generating an information extraction comprising a set of labels corresponding to the set of information items.

Abstract: One or more computing devices, systems, and/or methods for generating a video in a target language are provided. In an example, a first video, in which a first speaker speaks in a first language, is identified. A translated transcript in a second language is determined. The translated transcript is indicative of a translation of speech spoken by the first speaker in the first video. Based upon the translated transcript and a speaker profile associated with a second speaker, first audio, including an auditory representation of the translated transcript being spoken in a voice of the second speaker, is generated. Based upon the first video and the first audio, a second video, in which mouth movements of the first speaker are aligned with speech of the auditory representation of the first audio, is generated.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The disclosed systems and methods provide a novel framework that provides on-device functionality to user devices for localized content ranking, modification and rendering. The disclosed systems and methods provide functionality for on-device personalization in a real-time, secure and network anonymous manner. Rather than exposing a user's data to the network for content tailoring, the disclosed framework performs the ranking and content manipulation locally on the user's device. The disclosed framework enables locally (on-device) built, updated and hosted user profiles to be used to tailor received content for display on a user device. This ensures the integrity of the personalization while maintaining security for the user's personalized data and activities.

Abstract: The instant system and methods solves the cold start problem through various systems and methods directed to aggregating user interaction data associated with a user over a period of time, scoring the user interaction data to determine at least one user interest relevance score and/or at least one surfacing user interest score for each of the plurality of user interaction types, wherein the scoring includes a time sensitive weighting scheme, and generating a user interest profile partition for each of the plurality of user interaction types based on the at least one user interest relevance score and/or the at least one surfacing user interest score.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: A method and system for using a proxy agent based access to documents and the corresponding summaries and its subsequent usage is disclosed. The method and system provides for retrieving a document, generating or retrieving summary, generating statistical parameters to judge the summary quality, using text segmentation to judge the quality of the summary, getting user rating input and using it to train a classifier, using the classifier to predict the rating of a summary, displaying the summary along with its rating, and optionally overlaying the summary display with relevant advertising and thus prevent denial of information/information overload and stimulating accelerated learning.

Abstract: A method and system for generating answers to questions based on electronic data summary which is itself derived on context and semantics of a corpus of authoritative documents and its subsequent usage is disclosed.

Abstract: A method and system for generating electronic data summary based on context and semantics of the document and its subsequent usage is disclosed. The method and system provides for generating a taxonomy of concepts, assigning unique-identifiers and weights to the taxonomy concepts using a given corpus of electronic data, using the taxonomy to identify the semantics of the document to be summarized, selecting text from a given document based on the weights of unique-identifiers in the taxonomy, generation of a list of semantic-structures and pruning of the list based upon an entropy threshold, generation of summary from the list of semantic-structures, generation of a topic summary from a given list of similar summaries, publishing of the summary in a known format, and usage of the summary to prevent denial of information.

Abstract: A method and system for searching location based information on a mobile device is disclosed. The method and system provides for location based resource information retrieval, processing retrieved resource information based on probability of finding them in the given location, a Peer to Peer recommendation system that combines other user's real time recommendations with archived recommendations, a virtual social network that creates a dynamic network consisting of user and user's acquaintances for refining the resource information, providing a refined set of search results, by considering user's privacy choices and personal preferences.