  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.
