Sentiment Analysis and Sentence Classification in Long Book-Search Queries

Author:

Htait AmalORCID,Fournier SébastienORCID,Bellot PatriceORCID

Publisher

Springer Nature Switzerland

Reference13 articles.

1. Bai, J., Nie, J.Y., Paradis, F.: Using language models for text classification. In: Proceedings of the Asia Information Retrieval Symposium, Beijing, China (2004)

2. Beitzel, S.M., Jensen, E.C., Frieder, O., Lewis, D.D., Chowdhury, A., Kolcz, A.: Improving automatic query classification via semi-supervised learning. In: Fifth IEEE International Conference on Data Mining (ICDM 2005), pp. 8–pp. IEEE (2005)

3. Blitzer, J., Dredze, M., Pereira, F.: Biographies, bollywood, boom-boxes and blenders: domain adaptation for sentiment classification. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 440–447 (2007)

4. Chen, T., Xu, R., He, Y., Wang, X.: Improving sentiment analysis via sentence type classification using BiLSTM-CRF and CNN. Expert Syst. Appl. 72, 221–230 (2017)

5. Collins, M.: Three generative, lexicalised models for statistical parsing. arXiv preprint cmp-lg/9706022 (1997)

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