Abstract: An information retrieval system, including a natural language parser (3) for parsing documents of a document space (1) to identify key terms of each document based on linguistic structure, and for parsing a search query to determine the search term, a feature extractor (4) for determining an importance score for terms of the document space (1) based on distribution of the terms in the document space (1), an index term generator (5) for generating index terms using the key terms identified by the parser (3) and the extractor (4) and having an importance score above a threshold level, and a query clarifier (16) for selecting from the index terms, on the basis of the search term, index terms for selecting at least one document from the document space (1). A speech recognition engine (12) is used to generate the query, and a bi-gram language module (6) generates grammar rules for the speech recognition engine (12) using the index terms.

Abstract: An information retrieval system including a natural language parser (3) for parsing documents of a document space (1) to identify key terms of each document based on linguistic structure, and for parsing a search query to determine the search term, a feature extractor (4) for determining an importance score for terms of the document space based on distribution of the terms in the document space, an index term generator (5) for generating index terms using the key terms identified by the parser and the extractor and having an importance score above a threshold level, and a query clarifier (16) for selecting from the index terms, on the basis of the search term, index terms for selecting a document from the document space. A speech recognition engine (12) generates the query, and a bi-gram language module (6) generates grammar rules for the speech recognition engine using the index terms.

Abstract: A search engine and system for data, such as Internet web pages, including a query analyser for processing a query to assign respective weights to terms of the query and to generate a query vector including the weights, and an index network responsive to the query vector to output at least one index to data in response to the query. The index network is a self-generating neural network built using training examples derived from a feature extractor. The feature extractor is used during both the search and training phase. A clusterer is used to group search results.

Abstract: A search engine and system for data, such as Internet web pages, including a query analyser for processing a query to assign respective weights to terms of the query and to generate a query vector including the weights, and an index network responsive to the query vector to output at least one index to data in response to the query. The index network is a self-generating neural network built using training examples derived from a feature extractor. The feature extractor is used during both the search and training phase. A clusterer is used to group search results.

Abstract: A search engine and system for data, such as Internet web pages, including a query analyser for processing a query to assign respective weights to terms of the query and to generate a query vector including the weights, and an index network responsive to the query vector to output at least one index to data in response to the query. The index network is a self-generating neural network built using training examples derived from a feature extractor. The feature extractor is used during both the search and training phase. A clusterer is used to group search results.

Abstract: An information retrieval system including a natural language parser (3) for parsing documents of a document space (1) to identify key terms of each document based on linguistic structure, and for parsing a search query to determine the search term, a feature extractor (4) for determining an importance score for terms of the document space (1) based on distribution of the terms in the document space (1), an index term generator (5) for generating index terms using the key terms identified by the parser (3) and the extractor (4) and having an importance score above a threshold level, and a query clarifier (16) for selecting from the index terms, on the basis of the search term, index terms for selecting at least one document from the document space (1). A speech recognition engine (12) is used to generate the query, and a bi-gram language module (6) generates grammar rules for the speech recognition engine (12) using the index terms.