Springer Verlag;Cham: Springer International Publishing
Abstract:
摘要： In this paper, we present our system that participated in the Polarity Detection task, the elementary task in the ESWC-14 Challenge on Concept-Level Sentiment Analysis. In addition to traditional Bag-of-Words features, we also employ state-of-the-art Sentic API to extract concepts from documents to generate Bag-of-Sentiment-Concepts features. Our previous work SentiConceptNet serves as the reference concept-based sentiment knowledge base for concept-level sentiment analysis. Experimental results on our development set show that adding Bag-of-Sentiment-Concepts can improve the accuracy by 1.3 %, indicating the benefit of concept-level sentiment analysis. Our demo website is located at http://140.115.51.136:5000. 出版者： Cham: Springer International Publishing 出版日期： 2014 出處： Communications in Computer and Information Science, 2014, p.53-58 資源來源： Springer Books 版權： Springer International Publishing Switzerland 2014 識別號： ISSN: 1865-0929 識別號： ISBN: 3319120239 識別號： ISBN: 9783319120232 識別號： EISSN: 1865-0937 識別號： EISBN: 9783319120249 識別號： EISBN: 3319120247 識別號： DOI: 10.1007/978-3-319-12024-9_7
