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
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
Co-clustering based classification for out-of-domain documents
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A two-stage approach to domain adaptation for statistical classifiers
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Multilingual subjectivity analysis using machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Co-training for cross-lingual sentiment classification
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
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
Is machine translation ripe for cross-lingual sentiment classification?
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Cross-Lingual Adaptation Using Structural Correspondence Learning
ACM Transactions on Intelligent Systems and Technology (TIST)
Bilingual co-training for sentiment classification of chinese product reviews
Computational Linguistics
Translation model based cross-lingual language model adaptation: from word models to phrase models
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Lost in translation: viability of machine translation for cross language sentiment analysis
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
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In this paper, we study the problem of using an annotated corpus in English for the same natural language processing task in another language. While various machine translation systems are available, automated translation is still far from perfect. To minimize the noise introduced by translations, we propose to use only key 'reliable" parts from the translations and apply structural correspondence learning (SCL) to find a low dimensional representation shared by the two languages. We perform experiments on an English-Chinese sentiment classification task and compare our results with a previous cotraining approach. To alleviate the problem of data sparseness, we create extra pseudo-examples for SCL by making queries to a search engine. Experiments on real-world on-line review data demonstrate the two techniques can effectively improve the performance compared to previous work.