On Learning Parsimonious Models for Extracting Consumer Opinions
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 3 - Volume 03
A novel refinement approach for text categorization
Proceedings of the 14th ACM international conference on Information and knowledge management
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Using Cross-Document Random Walks for Topic-Focused Multi-Document
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
A novel scheme for domain-transfer problem in the context of sentiment analysis
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Using unlabeled data to handle domain-transfer problem of semantic detection
Proceedings of the 2008 ACM symposium on Applied computing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
An effective refinement strategy for KNN text classifier
Expert Systems with Applications: An International Journal
Negative training data can be harmful to text classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
MIEA: a mutual iterative enhancement approach for cross-domain sentiment classification
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Automatically extracting polarity-bearing topics for cross-domain sentiment classification
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
User-level sentiment analysis incorporating social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Biographies or blenders: which resource is best for cross-domain sentiment analysis?
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Taxonomy-based regression model for cross-domain sentiment classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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With the aim to deal with sentiment-transfer problem, we proposed a novel approach, which integrates the sentiment orientations of documents into the graph-ranking algorithm. We apply the graph-ranking algorithm using the accurate labels of old-domain documents as well as the "pseudo" labels of new-domain documents. Experimental results show that proposed algorithm could improve the performance of baseline methods dramatically for sentiment transfer.