MayAnd at SemEval-2016 Task 5: Syntactic and word2vec-based approach to aspect-based polarity detection in Russian.
MayAnd at SemEval-2016 Task 5: Syntactic and word2vec-based approach to aspect-based polarity detection in Russian.
Authors
Abstract
This paper describes aspect-based polarity detection system for Russian, used in aspect-based sentiment analysis task (ABSA) of SemEval-2016 (Task 5, subtask 1, slot 3). The system consists of two independent classifiers: for opinion target expressions and for implicit opinion target mentions. We introduce a set of standard unigram features together with more sophisticated ones: based on sentence syntactic structure and based on lemmas vector representation.
Being applied to Russian restaurant reviews, our system achieved best quality among four participants.
Edition
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). 2016. pp. 325-329.
Research Group
All publications during 2016
All publications