01850nas a2200217   4500008004100000245010200041210006900143260000900212300001400221490000600235520109100241653002801332653002601360653003401386653002001420653002001440100001701460700001701477700002101494856011701515       2010                        eng d00aExploiting multi-word similarity for retrieval in medical document collections: The TSRM approach0 aExploiting multiword similarity for retrieval in medical documen  c2010  a315 - 3210 v83 aIn this paper, we investigate on potential improvements to Information Retrieval (IR) models related to document representation and conceptual, topic retrieval, in medical document collections. We propose the TSRM1 (Term Similarity and Retrieval Model) approach, where document representations are based on multi-word domain terms, rather than mere single key-words, typically applied in traditional IR. The proposed representation is semantically compact and more efficient, being reduced to a limited number of meaningful multi-word terms (phrases), rather than large vectors of single-words, part of which may be void of distinctive content semantics. In computing document similarity, contrary to other state-of-theart methods examined in this work, TSRM adopts a knowledge poor solution, namely an approach which does not require any existing knowledge resources, such as ontologies, or thesauri. The evaluation of TSRM is based on OHSUMED, a standard TREC collection of medical documents and illustrated the effciency of TSRM over other well established general purpose IR models.10aDocument representation10aInformation retrieval10aMedical information retrieval10aTerm extraction10aTerm Similarity1 aDrymonas, E.1 aZervanou, K.1 aPetrakis, E.G.M.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960229245&partnerID=40&md5=f9f58b511661960f2a01ed0691084e33