A Graph-Based Approach for Sentiment Sentence Extraction

Authors:
Kazutaka Shimada;Daigo Hashimoto;Tsutomu Endo
Affiliations:
Department of Artificial Intelligence, Kyushu Institute of Technology, Fukuoka, Japan 820-8502;Department of Artificial Intelligence, Kyushu Institute of Technology, Fukuoka, Japan 820-8502;Department of Artificial Intelligence, Kyushu Institute of Technology, Fukuoka, Japan 820-8502
Venue:
New Frontiers in Applied Data Mining
Year:
2009

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Abstract

As the World Wide Web rapidly grows, a huge number of online documents are easily accessible on the Web. We obtain a huge number of review documents that include user's opinions for products. To classify the opinions is one of the hottest topics in natural language processing. In general, we need a large amount of training data for the classification process. However, construction of training data by hand is costly. In this paper, we examine a method of sentiment sentence extraction. This task is to classify sentences in documents into opinions and non-opinions. For the task, we use the Hierarchical Directed Acyclic Graph (HDAG) proposed by Suzuki et al. We obtained high accuracy in the sentiment sentence extraction task. The experimental result shows the effectiveness of the method based on the HDAG.