Abstract: A data processing system and method for validating a language model includes executing the language model to extract a plurality of strings from a set of documents and for each string, parsing the string to generate a plurality of tokens, lemmatizing the plurality of tokens, applying a part-of-speech label to the plurality of tokens, executing a filtering operation to obtain a plurality of filtered tokens, automatically building a weighted categorization rule based on the plurality of filtered tokens, applying the weighted categorization rule to the set of documents to identify one or more text spans from the set of documents, computing a relevancy score for each of the one or more text spans extracted from the set of documents, and selecting the one or more text spans extracted from the set of documents having the relevancy score greater than a predetermined threshold.

Abstract: A human language analyzer receives, at the human language analyzer, text data representing information in a human language. The human language analyzer receives a computer command for identifying a text data component of the text data. The computer command comprises at least two requirements for the text data component. The human language analyzer, responsive to identifying that the first requirement and the second requirement are met, locates the text data component from one of two clauses. A clause analyzer receives a clause request to locate clauses within text data representing information in a human language. The clause analyzer receives, responsive to a dependency request, token information in a token data set. The clause analyzer determines a location for each clause of the sentence portion in a hierarchy of clauses. The clause analyzer generates and outputs a new data set based on the token data set and the hierarchy of clauses.

Abstract: A human language analyzer receives, at the human language analyzer, text data representing information in a human language. The human language analyzer receives a computer command for identifying a text data component of the text data. The computer command comprises at least two requirements for the text data component. The human language analyzer, responsive to identifying that the first requirement and the second requirement are met, locates the text data component from one of two clauses. A clause analyzer receives a clause request to locate clauses within text data representing information in a human language. The clause analyzer receives, responsive to a dependency request, token information in a token data set. The clause analyzer determines a location for each clause of the sentence portion in a hierarchy of clauses. The clause analyzer generates and outputs a new data set based on the token data set and the hierarchy of clauses.

Abstract: A human language analyzer receives, at the human language analyzer, text data representing information in a human language. The human language analyzer receives a computer command for identifying a text data component of the text data. The computer command comprises at least two requirements for the text data component. The human language analyzer, responsive to identifying that the first requirement and the second requirement is met, locates the text data component from one of two clauses. A clause analyzer receives a clause request to locate clauses within text data representing information in a human language. The clause analyzer receives, responsive to a dependency request, token information in a token data set. The clause analyzer determines a location for each clause of the sentence portion in a hierarchy of clauses. The clause analyzer generates and outputs a new data set based on the token data set and the hierarchy of clauses.

Abstract: A method and system for performing automated biological identification. The system including a preprocessing module with a histogram transform for locally and globally enhancing biological data such as fingerprints. An enhancement module with a fast smoothing and enhancement function. A feature extraction module with a fingerprint oriented thinning function. A matching module with a resolution-enhanced Hough transform function for fingerprint registration and matching score function.