Concept-based retrieval and interpretation for large data sets

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Concept-based retrieval and interpretation for large data sets. Access to on-line information is growing at an exponential rate, fuelled by advances in computing and \r\ncommunications technologies. Current information retrieval methods are becoming ineffective due to \r\ntheir reliance on simple term-based methods, resulting in a massive number of matches, of which only \r\na small proportion are relevant. We address this problem by developing new matching algorithms which \r\nunderstand the underlying meaning of documents in database repositories - by building semantic \r\nstructures semi-automatically - and thus provide more relevant information to queries. \r\nThis project will be of great benefit to a multitude of end-users in medicine, history, law and many other disciplines.\r\n