Abstract: The present invention is a methodology for analyzing and evaluating a sample text, such as essay(s), or document(s). This methodology compares sample text to a reference essay(s), document(s), or text segment(s) within a reference essay or document. The methodology analyzes the amount of subject-matter information in the sample text, analyzes the relevance of subject matter information in the sample and evaluates the semantic coherence of the sample. This methodology presumes there is an underlying, latent semantic structure in the usage of words. The method parses and stores text objects and text segments from the sample text and reference text into a two-dimensional data matrix. A weight is computed for each text object and applied to each data matrix cell value. The method performs a singular value decomposition on the data matrix, which produces three trained matrices. The method computes a vector representation of the sample text and reference text using the three trained matrices.

Abstract: An information retrieval system is disclosed, wherein the system includes a plurality of text search engines based on substantially different computational searching techniques. By activating each search engine with input from a user information request, the output from each of the search engines is combined into a single list of information items. A ranking process ranks the information items in the combined list by utilizing information item ordering data also received from each of the search engines as to the relevance of the information items output by the search engine to the user's request. Thus, by providing higher rankings to those information items determined to be most relevant to the user's request by each of (or a majority of) the search engines, these information items have been found to be highly consistent in satisfying the user's request for information.

Abstract: The present invention is a system and method for retrieving segments of stored video programs using closed caption text data. The closed caption text data is extracted from video programming signals received by the invention. Text records based on the extracted closed caption data are generated. Each text record is derived from the closed caption data for a single continuous video segment to which the text record serves as an index or key in retrieving this video segment. Preferably, each text record (a) has sufficient content to adequately describe the content of the video segment to which it serves as an index; and (b) corresponds to a video segment focused on a small number of topics. To accomplish (a) and (b) the present invention generates each text record so that it has a predetermined maximum length and so that it is derived from the closed caption data for a single uninterrupted speaker.

Abstract: A methodology for retrieving textual data objects in a multiplicity of languages is disclosed. The data objects are treated in the statistical domain by presuming that there is an underlying, latent semantic structure in the usage of words in each language under consideration. Estimates to this latent structure are utilized to represent and retrieve objects. A user query is recouched in the new statistical domain and then processed in the computer system to extract the underlying meaning to respond to the query.

Abstract: A methodology for retrieving textual data objects is disclosed. The information is treated in the statistical domain by presuming that there is an underlying, latent semantic structure in the usage of words in the data objects. Estimates to this latent structure are utilized to represent and retrieve objects. A user query is recouched in the new statistical domain and then processed in the computer system to extract the underlying meaning to respond to the query.