Opinion Mining by Generating the Summaries of Users’ Reviews
Opinion mining is to categorize the opinion-oriented documents into positive or negative document sets according to their polarity. Previous approaches may cause the problem of high dimensionality of the vector. This paper we applied the technique of generating the summaries of the users’ reviews to solve this problem. After making a comparison with previous approaches, we prove that the use of this method can reduce the number of vector dimensions, consistent with the performance of previous approaches.
Unable to display preview. Download preview PDF.
- 1.Kamps, J., Marx, M., & Mokken, R.J. 2004. Using WordNet to measure semantic orientation of adjectives. Proceedings of the 4th International Conference on Language Resources and Evaluation: 1115–1118.Google Scholar
- 2.Marcus, M. P., Santorini, B.,& Marcinkiewicz, M. A. 1993. Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics, 19(2): 313–330.Google Scholar
- 3.Pang, B., Lee, L., & Vaithyanathan, S. 2002. Thumbs up?: opinion mining using machine learning techniques. Proceedings of the ACL-02 conference on Empirical methods in natural language processing: 79–86.Google Scholar
- 4.Hu, M., & Liu, B. 2004. Mining and summarizing customer reviews. Proceedings of the 10th ACM SIGKDD international conference on knowledge discovery and data mining: 168–177.Google Scholar
- 5.Zhuang, L., Jing, F., & Zhu, X. Y. 2006. Movie review mining and summarization. Proceedings of the 15th ACM international conference on information and knowledge management: 43–50.Google Scholar
- 6.Pang, B. & Lee, L. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. Proceedings of the 42nd annual meeting of the association for computational linguistics: 271–278.Google Scholar