A maximum entropy approach to natural language processing
Computational Linguistics
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Movie review mining and summarization
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Identifying sources of opinions with conditional random fields and extraction patterns
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Topic sentiment mixture: modeling facets and opinions in weblogs
Proceedings of the 16th international conference on World Wide Web
The utility of linguistic rules in opinion mining
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Adding redundant features for CRFs-based sentence sentiment classification
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
Identifying expressions of opinion in context
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Expanding domain sentiment lexicon through double propagation
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Comparison of feature-level learning methods for mining online consumer reviews
Expert Systems with Applications: An International Journal
Aspect extraction through semi-supervised modeling
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Cross-domain co-extraction of sentiment and topic lexicons
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Opinion target extraction using word-based translation model
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
How to evaluate opinionated keyphrase extraction?
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
One seed to find them all: mining opinion features via association
Proceedings of the 21st ACM international conference on Information and knowledge management
On the design of LDA models for aspect-based opinion mining
Proceedings of the 21st ACM international conference on Information and knowledge management
The FLDA model for aspect-based opinion mining: addressing the cold start problem
Proceedings of the 22nd international conference on World Wide Web
Adaptive co-training SVM for sentiment classification on tweets
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A probabilistic mixture model for mining and analyzing product search log
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Opinion target extraction using partially-supervised word alignment model
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
SemEval-2010 task 18: disambiguating sentiment ambiguous adjectives
Language Resources and Evaluation
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In this paper, we focus on object feature based review summarization. Different from most of previous work with linguistic rules or statistical methods, we formulate the review mining task as a joint structure tagging problem. We propose a new machine learning framework based on Conditional Random Fields (CRFs). It can employ rich features to jointly extract positive opinions, negative opinions and object features for review sentences. The linguistic structure can be naturally integrated into model representation. Besides linear-chain structure, we also investigate conjunction structure and syntactic tree structure in this framework. Through extensive experiments on movie review and product review data sets, we show that structure-aware models outperform many state-of-the-art approaches to review mining.