Abstract: Expanding the corpus of a question answering system. The question answering system is adapted to generate a candidate answer to a query. The candidate answer may be incorporated into the corpus of the question answering system if the candidate answer meets or exceeds a predetermined requirement. By expanding the corpus with material that has been determined to be useful for answering a query, for example, the corpus may be expanded automatically in an accurate and efficient manner.

Abstract: Expanding the corpus of a question answering system. The question answering system is adapted to generate a candidate answer to a query. The candidate answer may be incorporated into the corpus of the question answering system if the candidate answer meets or exceeds a predetermined requirement. By expanding the corpus with material that has been determined to be useful for answering a query, for example, the corpus may be expanded automatically in an accurate and efficient manner.

Abstract: A method for providing content-level data artifact recommendations can begin with the creation of a semantic library from the textual content of data artifacts by a newsworthy content recommendation engine. A base newsworthiness rating can be calculated using global newsworthiness parameters and behavioral functions that model newsworthy influences for each relationship contained in the semantic library. A user-specific search network can be generated that represents user-entered criteria and/or user task-related criteria. Within the semantic library, potential newsworthy semantic networks can be identified. Newsworthy content from each identified potential newsworthy semantic network can be dynamically determined based upon the base newsworthiness rating and a predefined newsworthiness threshold. The newsworthy content from the identified potential newsworthy semantic network can be related to the user-specific search network at the common node, creating a newsworthy content recommendation graph.

Abstract: A method for providing content-level data artifact recommendations can begin with the creation of a semantic library from the textual content of data artifacts by a newsworthy content recommendation engine. A base newsworthiness rating can be calculated using global newsworthiness parameters and behavioral functions that model newsworthy influences for each relationship contained in the semantic library. A user-specific search network can be generated that represents user-entered criteria and/or user task-related criteria. Within the semantic library, potential newsworthy semantic networks can be identified. Newsworthy content from each identified potential newsworthy semantic network can be dynamically determined based upon the base newsworthiness rating and a predefined newsworthiness threshold. The newsworthy content from the identified potential newsworthy semantic network can be related to the user-specific search network at the common node, creating a newsworthy content recommendation graph.