Word association norms, mutual information, and lexicography
Computational Linguistics
Independent component analysis: theory and applications
Independent component analysis: theory and applications
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Using WordNet and Lexical Operators to Improve Internet Searches
IEEE Internet Computing
Automatic discovery of similarity relationships through Web mining
Decision Support Systems - Web retrieval and mining
HelpfulMed: intelligent searching for medical information over the internet
Journal of the American Society for Information Science and Technology
Choosing the word most typical in context using a lexical co-occurrence network
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
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Lexical substitution as a task for WSD evaluation
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
A statistical model for near-synonym choice
ACM Transactions on Speech and Language Processing (TSLP)
Direct word sense matching for lexical substitution
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Characterising measures of lexical distributional similarity
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A review of ontology based query expansion
Information Processing and Management: an International Journal
Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
Information Processing and Management: an International Journal
A semantic-expansion approach to personalized knowledge recommendation
Decision Support Systems
A Latent Semantic Indexing-based approach to multilingual document clustering
Decision Support Systems
Psychiatric document retrieval using a discourse-aware model
Artificial Intelligence
Annotation and verification of sense pools in OntoNotes
Information Processing and Management: an International Journal
Near-synonym lexical choice in latent semantic space
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Discriminative training for near-synonym substitution
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Discovering latent topical structure by second-order similarity analysis
Journal of the American Society for Information Science and Technology
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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Despite their similar meanings, near-synonyms may have different usages in different contexts, and the development of algorithms that can verify whether near-synonyms do match their given contexts has been the focus of increasing concern. Such algorithms have many applications such as query expansion for information retrieval (IR), alternative word selection for writing support systems, and (near-)duplicate detection for text summarization. In this paper, we propose a framework that incorporates latent semantic analysis (LSA) and independent component analysis (ICA) to automatically select suitable near-synonyms according to the given context. LSA is used to discover useful latent features that do not frequently occur in the contexts of near-synonyms, and ICA is used to estimate a set of independent components by minimizing the dependence between features. An SVM classifier is then trained with the independent components for best near-synonym prediction. In experiments, we evaluate the proposed method on both Chinese and English sentences, and compare its performance to state-of-the-art supervised and unsupervised methods. Experimental results show that training on the independent components that contain useful contextual features with minimized term dependence can improve the classifiers' ability to discriminate among near-synonyms, thus yielding better performance.