Clustering Weblogs on the Basis of a Topic Detection Method

Authors

Fernando Perez-Tellez, Social Media Research Group, Institute of Technology, Tallaght, Dublin, IrelandFollow
David Pinto, Benemérita Universidad Autónoma de Puebla, MexicoFollow
John Cardiff, Technological University Dublin, Tallaght, Dublin, IrelandFollow
Paolo Rosso, Natural Language Engineering Lab, ELiRF, Universidad Pólitecnica de Valencia, SpainFollow

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE

Abstract

In recent years we have seen a vast increase in the volume of information published on weblog sites and also the creation of new web technologies where people discuss actual events. The need for automatic tools to organize this massive amount of information is clear, but the particular characteristics of weblogs such as shortness and overlapping vocabulary make this task difficult. In this work, we present a novel methodology to cluster weblog posts according to the topics discussed therein. This methodology is based on a generative probabilistic model in conjunction with a Self-Term Expansion methodology. We present our results which demonstrate a considerable improvement over the baseline.

DOI

https://doi.or/10.1007/978-3-642-15992-3_36

Recommended Citation

Perez-Tellez F., Pinto D., & Cardiff J. (2010). Clustering Weblogs on the Basis of a Topic Detection Method. Mexican Conference on Pattern Recognition in Lecture Notes in Computer Science,/i>, vol. 6256, pg. 342-351. https://doi.org/10.1007/978-3-642-15992-3_36