The Use of Topic Modeling with Regularization

Student: Zubrilina Olga

Supervisor: Nikolay Karpov

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 8

Year of Graduation: 2017

This paper is devoted to the basic approaches of topic modeling and to Additive Regularization of topic models(ARTM). In experiments EuroPal dataset was used (The Europarl parallel corpus is extracted from the proceedings of the European Parliament). To measure the quality of the topic model, a cross-language search is performed.

Full text (added May 22, 2017)

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