Query Refinement by Multi Word Term expansions and semantic synonymy

TL;DR

This paper presents TermWatch, a system that extracts and structures domain terms from large text corpora, enhancing query refinement through semantic clustering and network visualization, tested on extensive bibliographic data.

Contribution

The paper introduces TermWatch, a novel system combining linguistic term extraction, semantic clustering, and network structuring for improved query refinement.

Findings

Successfully extracted and structured over 367,000 terms from bibliographic abstracts.

Compared the automatically generated resource with an existing terminological database, demonstrating its effectiveness.

Enhanced understanding of domain concepts through network visualization of terms.

Abstract

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.