Opinion Analysis for NTCIR8 at POSTECH

NECLC at Multilingual Opinion Analysis Task in NTCIR8

In this paper, we briefly describe our machine-learning based method used in the NITCIR8 MOAT task, particularly, the opinioned sentence judgment subtask on both English side and Chinese side. We view this subtask as a binary classification problem and build a supervised-learning based framework. To extract meaningful sentiment features, we propose several n-gram patterns to assemble basic word...

English Opinion Analysis for NTCIR7 at POSTECH

We describe an opinion analysis system developed for Multilingual Opinion Analysis Task at NTCIR7. Given a topic and relevant newspaper articles, our system determines whether a sentence in the articles carries an opinion, if so, then extract the polarity and holder of the opinion. Our system uses subjectivity lexicons to score the sentiment weight of a word, in addition with a weight that refl...

WIA-Opinmine System in NTCIR-8 MOAT Evaluation

This paper presents WIA-Opinmine system developed by CUHK_Tsinghua Web Information Analysis (WIA) Virtual Research Center for NTCIR-8 MOAT Task. The system is deemed special due to three facts. Firstly, the system is able to handle Simplified Chinese and Traditional Chinese at the same time. A tool is developed to convert Traditional Chinese into Simplified Chinese before opinion analysis. Seco...

Best-Answer Selection Using a Machine Learning Tool at NTCIR8 CQA Pilot Task

Feature extraction in opinion mining through Persian reviews

Opinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which can play an important role in making major decisions in such area. In general, opinion mining extracts user reviews at three levels of document, sentence and feature. Opinion mining at the feature level is taken into consideration more than the other two levels d...