Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting knowledge from evaluative text
Proceedings of the 3rd international conference on Knowledge capture
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Using measures of semantic relatedness for word sense disambiguation
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Aspect-based extractive summarization of online reviews
Proceedings of the 2011 ACM Symposium on Applied Computing
Aspect ranking: identifying important product aspects from online consumer reviews
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning opinions in user-generated web content
Natural Language Engineering
Comparison of feature-level learning methods for mining online consumer reviews
Expert Systems with Applications: An International Journal
Semisupervised learning based opinion summarization and classification for online product reviews
Applied Computational Intelligence and Soft Computing
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We describe an architecture for organizing and summarizing consumer reviews about products that have been posted on specialized web sites. The core technology is based on the automatic extraction of product features for which we report experiments on two types of corpora. We thus show that NLP techniques can be fruitfully used in this context for helping consumers sort out the mass of information displayed in such contexts.