Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Class-based probability estimation using a semantic hierarchy
Computational Linguistics
Automatic semantic classification for Chinese unknown compound nouns
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Word classification based on combined measures of distributional and semantic similarity
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Unsupervised methods for developing taxonomies by combining syntactic and statistical information
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Semantic classification of Chinese unknown words
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Supersense tagging of unknown nouns in WordNet
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Supersense tagging of unknown nouns using semantic similarity
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Exploiting semantic role labeling, WordNet and Wikipedia for coreference resolution
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A method for automatic POS guessing of Chinese unknown words
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Discovering the discriminative views: measuring term weights for sentiment analysis
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
Textual entailment recognition based on dependency analysis and wordnet
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Induction of Semantic Classes Based on Coordinate Patterns
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Coarse lexical semantic annotation with supersenses: an Arabic case study
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
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Supersense tagging classifies unknown words into semantic categories defined by lexicographers and inserts them into a thesaurus. Previous studies on supersense tagging show that context-based methods perform well for English unknown words while structure-based methods perform well for Chinese unknown words. The challenge before us is how to successfully combine contextual and structural information together for supersense tagging of Chinese unknown words. We propose a simple yet effective approach to address the challenge. In this approach, contextual information is used for measuring contextual similarity between words while structural information is used to filter candidate synonyms and adjusting contextual similarity score. Experiment results show that the proposed approach outperforms the state-of-art context-based method and structure-based method.