Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Object Models from Semistructured Web Documents
IEEE Transactions on Knowledge and Data Engineering
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Aspect-based sentence segmentation for sentiment summarization
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Phrase dependency parsing for opinion mining
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Answering opinion questions on products by exploiting hierarchical organization of consumer reviews
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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In this paper, we propose to organize the aspects of a specific product into a hierarchy by simultaneously taking advantages of domain structure knowledge as well as consumer reviews. Based on the derived hierarchy, we generate a hierarchical organization of the consumer reviews based on various aspects of the product, and aggregate consumer opinions on the aspects. With such hierarchical organization, people can easily grasp the overview of consumer reviews and opinions on various aspects, as well as seek consumer reviews and opinions on any specific aspect by navigating through the hierarchy. We conduct evaluation on two product review data sets: Liu et al.'s data set containing 314 reviews for five products [2], and our review corpus which is collected from forum Web sites containing 60,786 reviews for five popular products. The experimental results demonstrate the effectiveness of our approach.