
Summary of the paper
Title 
Thematic Cohesion: Measuring Terms Discriminatory Power Toward Themes 
Authors 
Clément De Groc, Xavier Tannier and Claude De Loupy 
Abstract 
We present a new measure of thematic cohesion. This measure associates each term with a weight representing its discriminatory power toward a theme, this theme being itself expressed by a list of terms (a thematic lexicon). This thematic cohesion criterion can be used in many applications, such as query expansion, computerassisted translation, or iterative construction of domainspecific lexicons and corpora. The measure is computed in two steps. First, a set of documents related to the terms is gathered from the Web by querying a Web search engine. Then, we produce an oriented cooccurrence graph, where vertices are the terms and edges represent the fact that two terms cooccur in a document. This graph can be interpreted as a recommendation graph, where two terms occurring in a same document means that they recommend each other. This leads to using a random walk algorithm that assigns a global importance value to each vertex of the graph. After observing the impact of various parameters on those importance values, we evaluate their correlation with retrieval effectiveness. 
Topics 
Information Extraction, Information Retrieval 
Full paper 
Thematic Cohesion: Measuring Terms Discriminatory Power Toward Themes 
Bibtex 
@InProceedings{DEGROC14.991,
author = {Clément De Groc and Xavier Tannier and Claude De Loupy}, title = {Thematic Cohesion: Measuring Terms Discriminatory Power Toward Themes}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {2631}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {9782951740884}, language = {english} } 

