Integrating semantics into biomedical information retrieval
Integrating semantics into Biomedical Information Retrieval is concerned with studying the meaning of concepts and focusing on their relationships. We have used semantic document representation approach to applying domain-specific knowledge into the information retrieval system. Single and multi word concepts are extracted from the document using an external semantic structure UMLS Metathesaurus. Word sense disambiguation is performed on the extracted concepts to disambiguate different concept senses. And, the document is represented in the form of UMLS concepts. The documents and queries are represented in semantic space and fed to an information retrieval system to rank those documents, according to the given query. We have performed experiments on TREC 2014 CDS Task data and its 30 queries. Two types of retrieval techniques namely single word and multi word retrieval are experimented. The results obtained using conceptual information retrieval are compared with the results obtained using traditional term based retrieval. The conceptual IR approach proved better compared to term based IR system for the evaluation metrics MAP, P10 and RPrec. And, single word retrieval proved better compared to multi word retrieval technique for conceptual IR. Also, query expansion in conceptual IR system proved better compared to non query expanded conceptual IR system.
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