Abstract: A document retrieval is performed with similarities between documents in numeric data taken into consideration. To this end, generated is a set E of intervals in which each element of a set D of numeric values representing a feature A is included in any one of the intervals. Each numeric value in each document is indexed by assigning, with 1, an interval including an element x of the set D, and with 0, an interval without the element x. Each document data including numeric values is indexed by indexing its text part with term frequencies, and by indexing its numeric-value part with the above-described numeric value indexing scheme. By use of indices thus created for each of the document data, similarities between the document data are calculated using a vector space model or a probability model, and the document data are presented in order of similarity.

Abstract: A document retrieval is performed with similarities between documents in numeric data taken into consideration. To this end, generated is a set E of intervals in which each element of a set D of numeric values representing a feature A is included in any one of the intervals. Each numeric value in each document is indexed by assigning, with 1, an interval including an element x of the set D, and with 0, an interval without the element x. Each document data including numeric values is indexed by indexing its text part with term frequencies, and by indexing its numeric-value part with the above-described numeric value indexing scheme. By use of indices thus created for each of the document data, similarities between the document data are calculated using a vector space model or a probability model, and the document data are presented in order of similarity.

Abstract: Both a first kind of terms and a second kind of terms are designated. A user desires to obtain a relationship between these terms. By employing relations between these terms having been previously stored in a storage in advance, the manner in which these terms are correlated is dynamically displayed, while nodes and edges are gradually increased. In this manner, relations are easily found for concepts (terms) that seem not to be correlated, and an efficient search can also be performed.

Abstract: To provide a summary of a search result in an associative search system based on multiple viewpoints. By indexing one document database in plural ways, a summary of a search result can be displayed from multiple viewpoints. By managing documents in indexed versions of the document database by common identifiers, summaries of a document set obtained as a search result can be created using the different indexes.

Abstract: A system for effectively collecting, without omissions, spelling variations centering on particular technical terms occurring in documents. In advance, the system sorts technical terms considered to be potential spelling variations from among a large-scale collection of terms. By measuring the edit distance adjusted for the cost of the terms that are potential spelling variations, the system can collect terms considered spelling variations from among the potential spelling variation terms with a high degree of accuracy.

Abstract: New information is extracted efficiently and exhaustively to predict the function of genes or proteins. First, known-sequence data with high relevance to a search object sequence or structure information is obtained using a sequence database. Then, documents relevant to the resultant known-sequence data are retrieved, using a document database. Feature words common to a plurality of documents extracted are extracted and outputted.