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

Amal Htait (1, 2, 3) , Sébastien Fournier (3) , Patrice Bellot (3, 2)

1 CLEO - Centre pour l'édition électronique ouverte
2 LIS - Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon)
3 R2I - Recherche d’information et Interactions

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.

Domaines: Informatique [cs]; Recherche d'information [cs.IR]; Traitement du texte et du document

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