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Sentiment Analysis and Sentence Classification in Long Book-Search Queries

Abstract : Handling long queries can involve either reducing its size by retaining only useful sentences, or decomposing the long query into several short queries based on their content. A proper sentence classification improves the utility of these procedures. Can Sentiment Analysis has a role in sentence classification? This paper analysis the correlation between sentiment analysis and sentence classification in long book-search queries. Also, it studies the similarity in writing style between book reviews and sentences in book-search queries. To accomplish this study, a semi-supervised method for sentiment intensity prediction, and a language model based on book reviews are presented. In addition to graphical illustrations reflecting the feedback of this study, followed by interpretations and conclusions.
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Contributor : Amal Htait <>
Submitted on : Thursday, October 17, 2019 - 11:44:04 AM
Last modification on : Thursday, March 5, 2020 - 5:49:23 PM
Document(s) archivé(s) le : Saturday, January 18, 2020 - 1:38:35 PM


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  • HAL Id : hal-02318630, version 1



Amal Htait, Sébastien Fournier, Patrice Bellot. Sentiment Analysis and Sentence Classification in Long Book-Search Queries. CICLing, Apr 2019, La Rochelle, France. ⟨hal-02318630⟩



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