Abstract: To identify and describe one or more topics in one or more documents in a document set, a term set process creates a basic term set from the document set where the term set comprises one or more basic terms of one or more words in the document. A document vector process then creates a document vector for each document. The document vector has a document vector direction representing what the document is about. A topic vector process then creates one or more topic vectors from the document vectors. Each topic vector has a topic vector direction representing a topic in the document set. A topic term set process creates a topic term set for each topic vector that comprises one or more of the basic terms describing the topic represented by the topic vector. Each of the basic terms in the topic term set associated with the relevancy of the basic term. A topic-document relevance process creates a topic-document relevance for each topic vector and each document vector.

Abstract: A method for compressing and decompressing integer-vector data by which N-dimensional integer vectors are compressed efficiently and by which a vector that satisfies a specific condition can be quickly decompressed and extracted. The method for compressing integer-vector data, which are represented as an N-dimensional integer vector set T, into an N-dimensional integer vector set T', comprises the steps of: converging a distribution of an i-th component (i is a component number selected from a range wherein i<N) of each vector that belongs to the set T by using a transformation function; and adding information concerning the i-th component to a j-th component (j is a component number selected from a range wherein j>i) in consonance with convergence.

Abstract: A system and a method for searching does not rely on prior compiled vocabulary information or grammatical information to perform a search. The search may accommodate new words or phrases, and perform a document search using a request of a user for document search. A unique character string is extracted from an input document and a similarity search is performed by using the unique character string. The extraction of the unique character string is performed by calculating and evaluating an amount of feature of a character string through comparison between appearance frequency appearing in the input document and appearance frequency in a set of documents to be searched. Then, the extracted unique character string is used as the basis for the search. Documents found by the search are evaluated and arranged in the order of evaluation.

Abstract: A system and method for searching a large volume of data stored in a disk in, for example, document file format at a high speed while allowing desired ambiguity. The present invention provides a character string search scheme which enables a user to optionally designate the degree of ambiguity for a character string to be searched. The present invention also provides an index structure for implementing a character string search scheme which enables a user of the search scheme to optionally designate the degree of ambiguity for a character string to be searched. The present invention also provides a character string search scheme which enables the scheme to perform searches in a manner close to human feeling by ambiguity search. Details of the manner in which such enablements are implemented are found in the detailed specification.