상세정보
학술대회
CNN based Sentence Classification with Semantic Features using Word Clustering
- 발행일
- 201810
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.484-488
- 협약과제
- 18HS3700, 언어학습을 위한 자유발화형 음성대화처리 원천기술 개발, 이윤근
- 초록
- Text classification is one of the natural language processing (NLP) methods that assigns texts to one or more categories. In this paper, we propose a text classification method based on deep neural networks and word clustering. We also provide analysis on the effects of the number of channels, the way of converting the cluster information to a vector, and the update method of the input channel during learning with baseline. To show the effectiveness of our approach, we apply the method to the TREC question dataset and Movie Review dataset. From the results, we confirm that semantic features from word clustering is able to increase the classification accuracy by 1.96%.
- KSP 제안 키워드
- Classification method, Cluster information, Deep neural network(DNN), Movie Review, Natural Language Processing, Sentence Classification, Word clustering, classification accuracy, semantic features, text classification