Abstract: A computer-implemented method for processing documents in a document database includes generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query, and processing vocabulary words based upon occurrences thereof in at least some of the retrieved documents. Respective relevancies of the vocabulary words based on the occurrences thereof and the user search query are generated. A re-ranking of the retrieved documents is generated based on the relevancies of the vocabulary words.

Abstract: A method for processing documents in a document database includes determining vocabulary words for each document, and determining a respective relevancy for each vocabulary word based upon occurrences thereof in all of the documents. Similarities are determined between the documents based upon the vocabulary words and their respective relevancies. At least one domain identification is determined for the documents based upon the determined similarities.

Abstract: A computer-implemented method for processing documents in a document database includes generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query, and processing vocabulary words based upon occurrences thereof in at least some of the retrieved documents. Respective relevancies of the vocabulary words based on the occurrences thereof and the user search query are generated. A re-ranking of the retrieved documents is generated based on the relevancies of the vocabulary words.

Abstract: A computer-implemented method for processing documents in a multi-lingual document database includes generating an initial ranking of retrieved multi-lingual documents using an information retrieval system and based upon a user search query, and processing vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents. Respective relevancies of the vocabulary words based on the occurrences thereof and the user search query are generated. A re-ranking of the retrieved multi-lingual documents is generated based on the relevancies of the vocabulary words.

Abstract: An information retrieval and visualization system utilizes multiple search engines for retrieving documents from a document database based upon user input queries. Search engines include an n-gram search engine and a vector space model search engine using a neural network training algorithm. Each search engine produces a common mathematical representation of each retrieved document. The retrieved documents are then combined and ranked. Mathematical representations for each respective document is mapped onto a display. Information displayed includes a three-dimensional display of keywords from the user input query. The three-dimensional visualization capability based upon the mathematical representation of information within the information retrieval and visualization system provides users with an intuitive understanding, with relevance feedback/query refinement techniques that can be better utilized, resulting in higher retrieval accuracy (precision).

Abstract: An information retrieval and visualization system utilizes multiple search engines for retrieving documents from a document database based upon user input queries. Search engines include an n-gram search engine and a vector space model search engine using a neural network training algorithm. Each search engine produces a common mathematical representation of each retrieved document. The retrieved documents are then combined and ranked. Mathematical representations for each respective document is mapped onto a display. Information displayed includes a three-dimensional display of keywords from the user input query. The three-dimensional visualization capability based upon the mathematical representation of information within the information retrieval and visualization system provides users with an intuitive understanding, with relevance feedback/query refinement techniques that can be better utilized, resulting in higher retrieval accuracy (precision).

Abstract: An information retrieval and visualization system utilizes multiple search engines for retrieving documents from a document database based upon user input queries. Search engines include an n-gram search engine and a vector space model search engine using a neural network training algorithm. Each search engine produces a common mathematical representation of each retrieved document. The retrieved documents are then combined and ranked. Mathematical representations for each respective document is mapped onto a display. Information displayed includes a three-dimensional display of keywords from the user input query. The three-dimensional visualization capability based upon the mathematical representation of information within the information retrieval and visualization system provides users with an intuitive understanding, with relevance feedback/query refinement techniques that can be better utilized, resulting in higher retrieval accuracy (precision).

Abstract: An information retrieval and visualization system utilizes multiple search engines for retrieving documents from a document database based upon user input queries. Search engines include an n-gram search engine and a vector space model search engine using a neural network training algorithm. Each search engine produces a common mathematical representation of each retrieved document. The retrieved documents are then combined and ranked. Mathematical representations for each respective document is mapped onto a display. Information displayed includes a three-dimensional display of keywords from the user input query. The three-dimensional visualization capability based upon the mathematical representation of information within the information retrieval and visualization system provides users with an intuitive understanding, with relevance feedback/query refinement techniques that can be better utilized, resulting in higher retrieval accuracy (precision).