Co-clustering documents and words using bipartite spectral graph partitioning
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
K-means clustering via principal component analysis
ICML '04 Proceedings of the twenty-first international conference on Machine learning
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
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
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
The Journal of Machine Learning Research
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
A high-performance semi-supervised learning method for text chunking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Co-clustering based classification for out-of-domain documents
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Opinion integration through semi-supervised topic modeling
Proceedings of the 17th international conference on World Wide Web
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Domain adaptation of natural language processing systems
Domain adaptation of natural language processing systems
Document-Word Co-regularization for Semi-supervised Sentiment Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Latent space domain transfer between high dimensional overlapping distributions
Proceedings of the 18th international conference on World wide web
Rated aspect summarization of short comments
Proceedings of the 18th international conference on World wide web
EigenTransfer: a unified framework for transfer learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Extracting discriminative concepts for domain adaptation in text mining
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Knowledge transformation for cross-domain sentiment classification
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
IEEE Transactions on Knowledge and Data Engineering
Three challenges in data mining
Frontiers of Computer Science in China
Predictive distribution matching SVM for multi-domain learning
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Aspect and sentiment unification model for online review analysis
Proceedings of the fourth ACM international conference on Web search and data mining
Sentence-level contextual opinion retrieval
Proceedings of the 20th international conference companion on World wide web
Realtime social sensing of support rate for microblogging
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
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
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Cross-lingual sentiment classification via bi-view non-negative matrix tri-factorization
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
A cross-domain adaptation method for sentiment classification using probabilistic latent analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
Domain customization for aspect-oriented opinion analysis with multi-level latent sentiment clues
Proceedings of the 20th ACM international conference on Information and knowledge management
Bilingual co-training for sentiment classification of chinese product reviews
Computational Linguistics
A new domain adaptation method based on rules discovered from cross-domain features
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
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
A generate-and-test method of detecting negative-sentiment sentences
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Source-selection-free transfer learning
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Sentiment detection with auxiliary data
Information Retrieval
Multi-domain active learning for text classification
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Information Retrieval on the Blogosphere
Foundations and Trends in Information Retrieval
Transverse subjectivity classification
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Content-based retrieval for heterogeneous domains: domain adaptation by relative aggregation points
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Recognizing arguing subjectivity and argument tags
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
Unifying local and global agreement and disagreement classification in online debates
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
Transfer joint embedding for cross-domain named entity recognition
ACM Transactions on Information Systems (TOIS)
Unsupervised feature adaptation for cross-domain NLP with an application to compositionality grading
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Generating contextualized sentiment lexica based on latent topics and user ratings
Proceedings of the 24th ACM Conference on Hypertext and Social Media
Proceedings of the 2013 International Conference on Software Engineering
Cross-media sentiment classification and application to box-office forecasting
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
A partially supervised cross-collection topic model for cross-domain text classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Adaptive co-training SVM for sentiment classification on tweets
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Taxonomy-based regression model for cross-domain sentiment classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
TISA: topic independence scoring algorithm
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Analyzing, Detecting, and Exploiting Sentiment in Web Queries
ACM Transactions on the Web (TWEB)
Instance selection and instance weighting for cross-domain sentiment classification via PU learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Sentiment topic models for social emotion mining
Information Sciences: an International Journal
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Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditional classification algorithms can be used to train sentiment classifiers from manually labeled text data, the labeling work can be time-consuming and expensive. Meanwhile, users often use some different words when they express sentiment in different domains. If we directly apply a classifier trained in one domain to other domains, the performance will be very low due to the differences between these domains. In this work, we develop a general solution to sentiment classification when we do not have any labels in a target domain but have some labeled data in a different domain, regarded as source domain. In this cross-domain sentiment classification setting, to bridge the gap between the domains, we propose a spectral feature alignment (SFA) algorithm to align domain-specific words from different domains into unified clusters, with the help of domain-independent words as a bridge. In this way, the clusters can be used to reduce the gap between domain-specific words of the two domains, which can be used to train sentiment classifiers in the target domain accurately. Compared to previous approaches, SFA can discover a robust representation for cross-domain data by fully exploiting the relationship between the domain-specific and domain-independent words via simultaneously co-clustering them in a common latent space. We perform extensive experiments on two real world datasets, and demonstrate that SFA significantly outperforms previous approaches to cross-domain sentiment classification.