Sentiment Analysis and Sentence Classification in Long Book-Search Queries - Archive ouverte HAL
Communication Dans Un Congrès Année : 2019

Sentiment Analysis and Sentence Classification in Long Book-Search Queries

Analyse de sentiments et classification des phrases dans les longues requêtes de recherche de livres

Résumé

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.
Fichier principal
Vignette du fichier
Amal_Htait_CICLing_2019.pdf (665.25 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02318630 , version 1 (17-10-2019)

Identifiants

  • HAL Id : hal-02318630 , version 1

Citer

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

Partager

More