A High Precision Method for Aspect Extraction in Russian.

Authors

Mayorov V., Andrianov I., Astrakhantsev N., Avanesov V., Kozlov I., Turdakov D.

Abstract

This paper presents a work carried out by ISPRAS on aspect extraction task at SentiRuEval 2015. Our team submitted one run for Task A and Task B and got best precision for both tasks for all domains among all participants. Our method also showed the best F1-measure for exact aspect term matching for task A for automobile domain and both for Task A and Task B for restaurant domain. The method is based on sequential classification of tokens with SVM. It uses local, global, syntactic-based, GloVe, topic modeling and automatic term recognition features. In this paper we also present evaluation of significance of different feature groups for the task.

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Edition

Computational Linguistics and Intellectual Technologies (Proceedings of the Annual International Conference “Dialogue”). Issue 14(21). Volume 2. 2015. pp. 34-43.

Research Group

Information Systems

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