A vector space model for automatic indexing
Communications of the ACM
Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic induction of FrameNet lexical units
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A structured vector space model for word meaning in context
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Towards open-domain Semantic Role Labeling
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
UNITOR: combining semantic text similarity functions through SV regression
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
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Empirical distributional methods account for the meaning of syntactic structures by combining word vectors according to algebraic operators. In this paper, a novel approach for semantic composition based on space projection techniques over lexical vector representations is proposed. In line with the principle of compositionality, the meaning of a phrase is modeled in terms of the subset of properties shared by co-occurring words. Syntactic bi-grams are thus projected in the so called Support Subspace, corresponding to such properties. State-of-the-art results are achieved in a well known phrase similarity task, used as a benchmark for this class of methods.