We developed a system, TermWatch (https://stid-bdd.iut.univ-metz.fr/TermWatch/index.pl), which combines a linguistic extraction of terms, their structuring into a terminological network with a clustering algorithm. In this paper we explore its ability in integrating the most promising aspects of the studies on query refinement: choice of meaningful text units to cluster (domain terms), choice of tight semantic relations with which to cluster terms, structuring of terms in a network enabling abetter perception of domain concepts. We have run this experiment on the 367 645 English abstracts of PASCAL 2005-2006 bibliographic database (http://www.inist.fr) and compared the structured terminological resource automatically build by TermWarch to the English segment of TermScience resource (http://termsciences.inist.fr/) containing 88 211 terms.