A bootstrapping approach for robust topic analysis
Résumé
Topic analysis is important for a lot of applications dealing with texts, such as text summarization or information extraction. But it can be done with a great precision only if it relies on structured knowledge, which is difficult to produce on a large scale. In this article, we propose using bootstrapping in order to solve this problem: a first topic analysis based on a weakly structured source of knowledge, a collocation network, is used for learning explicit topic representations that then support a more precise and a more reliable topic analysis.