원문정보
초록
영어
Sentiment analysis of reviews has been the focus of recent research, which also has been attempted in different domains such as product reviews, movie reviews, and customer feedback reviews. Most sentiment analysis of reviews focused on extracting overall evaluation for a single product which makes difficult for a customer to know all the features of product and make a decision. Thus, mining this data, identifying the user opinions about different features and classify them is an important task. This paper is devoted to identify opinion object from short comments, and analyze sentiment of product based on features-level. CRFs model based on word embedding feature is adopted by identifying opinion object, which obtains a satisfied results. In addition, calculate rules based on syntax parsing are proposed to accomplish features-level sentiment analysis which extracts user’s opinion on many aspects. Experimental results using short comments of movies show the effectiveness of our approach.
목차
1. Introduction
2. Approach Overview
3. Opinion Objects Identification
3.1. Conditional Random Fields Model
3.2. Features Selection for CRFs
3.3. Data and Model Training
3.4. Results and Observations
4. Sentiment Analysis
4.1. Syntax Analysis
4.2. Features-Level Sentiment Analysis
5. Conclusions and Future Work
References