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, computer-assisted translation, or iterative construction of domain-specific 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 co-occurrence graph, where vertices are the terms and edges represent the fact that two terms co-occur 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 = {26-31}, 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 = {978-2-9517408-8-4}, language = {english} } |