@inbook{cd28a57a08ec4964a48bc5c07586f813,
title = "Polarity detection of online reviews using sentiment concepts: NCU IISR team at ESWC-14 Challenge on Concept-Level Sentiment Analysis",
abstract = "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.",
keywords = "Concept-level sentiment analysis, Polarity detection of online reviews, Sentiment concepts",
author = "Chung, {Jay Kuan Chieh} and Wu, {Chi En} and Tsai, {Richard Tzong Han}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.",
year = "2014",
doi = "10.1007/978-3-319-12024-9_7",
language = "???core.languages.en_GB???",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "53--58",
editor = "{Di Noia}, Tommaso and Valentina Presutti and Recupero, {Diego Reforgiato} and Iv{\'a}n Cantador and Christoph Lange and Christoph Lange and Anna Tordai and Christoph Lange and Milan Stankovic and Erik Cambria and {Di Iorio}, Angelo",
booktitle = "Semantic Web Evaluation Challenge - SemWebEval 2014 at ESWC 2014, Revised Selected Papers",
}