Abstract: A non-transitory computer readable storage medium includes instructions to collect explicit feedback from a user regarding user content preferences. Multiple data sources are monitored. Topics associated with the multiple data sources are classified. The importance of the topics to the user is characterized. Content is delivered to the user when a selected topic exceeds an importance threshold for the user. Implicit feedback from the user that characterizes refined user content preferences is tracked. The instructions to characterize the importance of topics evaluates the explicit feedback and the implicit feedback.

Abstract: A non-transitory computer readable storage medium includes instructions to collect explicit feedback from a user regarding user content preferences. Multiple data sources are monitored. Topics associated with the multiple data sources are classified. The importance of the topics to the user is characterized. Content is delivered to the user when a selected topic exceeds an importance threshold for the user. Implicit feedback from the user that characterizes refined user content preferences is tracked. The instructions to characterize the importance of topics evaluates the explicit feedback and the implicit feedback.

Abstract: A non-transitory computer readable storage medium includes instructions to maintain an original training set of labeled documents, where the labeled documents correspond to a variety of topics. A new labeled document corresponding to a new topic is received. The original training set of labeled documents is modulated such that the new labeled document is over-represented with respect to the original training set. This results in a modulated training set. A classifier is trained with the modulated training set to form a trained classifier.

Abstract: A non-transitory computer readable storage medium includes instructions to collect explicit feedback from a user regarding user content preferences. Multiple data sources are monitored. Topics associated with the multiple data sources are classified. The importance of the topics to the user is characterized. Content is delivered to the user when a selected topic exceeds an importance threshold for the user. Implicit feedback from the user that characterizes refined user content preferences is tracked. The instructions to characterize the importance of topics evaluates the explicit feedback and the implicit feedback.

Abstract: A non-transitory computer readable storage medium includes instructions to maintain an original training set of labeled documents, where the labeled documents correspond to a variety of topics. A new labeled document corresponding to a new topic is received. The original training set of labeled documents is modulated such that the new labeled document is over-represented with respect to the original training set. This results in a modulated training set. A classifier is trained with the modulated training set to form a trained classifier.

Abstract: A natural language information querying system includes an indexing facility configured to automatically generate indices of updated textual sources based on one or more predefined grammars and a database coupled to the indexing facility to store the indices for subsequent searching.

Abstract: A natural language information querying system includes an indexing facility configured to automatically generate indices of updated textual sources based on one or more predefined grammars and a database coupled to the indexing facility to store the indices for subsequent searching.