Multilingual probabilistic topic modeling and its applications in web mining and search

Authors:
Marie-Francine Moens;Ivan Vulié
Affiliations:
KU Leuven, Heverlee, Belgium;KU Leuven, Heverlee, Belgium
Venue:
Proceedings of the 7th ACM international conference on Web search and data mining
Year:
2014

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Abstract

Multilingual topic models are a fairly novel group of unsupervised, language-independent and generative machine learning models. This tutorial covers all key aspects of their probabilistic framework and demonstrates how to easily integrate these models into frameworks for cross-lingual and multilingual Web mining and search.