Topchat: encyclopedia-based topic identification from chat logs

Abstract

Textual conversations on the Internet, such us chat rooms or instant messaging services, have become an excellent source of data for semantic analysis. In particular, potential user interests or user-related topics could be extracted from these conversations for personalization purposes. In this work, we present a novel method for topic detection from chat logs. First, we de ned the generic structure of the process. Then, a variety of text-mining techniques was evaluated in each step of the process. Stemming, synonyms, POS tagging and named entities recognition are examples of these techniques. Encouraging experimental results from a comparative evaluation procedure, allow us to determine the most suitable combination of techniques for the problem.