Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
Class-based probability estimation using a semantic hierarchy
Computational Linguistics
Automatic labeling of semantic roles
Computational Linguistics
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Structural ambiguity and lexical relations
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Disambiguating Nouns, Verbs, and Adjectives Using Automatically Acquired Selectional Preferences
Computational Linguistics
Similarity of Semantic Relations
Computational Linguistics
Scaling distributional similarity to large corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Semantic taxonomy induction from heterogenous evidence
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Dependency-Based Construction of Semantic Space Models
Computational Linguistics
Aligning features with sense distinction dimensions
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Introduction to Information Retrieval
Introduction to Information Retrieval
A structured vector space model for word meaning in context
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
A study on similarity and relatedness using distributional and WordNet-based approaches
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Speaking through pictures: images vs. icons
Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility
BagPack: a general framework to represent semantic relations
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Multi-prototype vector-space models of word meaning
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Nonparametric Bayesian word sense induction
TextGraphs-6 Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing
GEMS '11 Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics
Unsupervised learning of selectional restrictions and detection of argument coercions
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Probabilistic models of similarity in syntactic context
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Cross-cutting models of lexical semantics
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improving word representations via global context and multiple word prototypes
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Statistical metaphor processing
Computational Linguistics
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We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to inferring distributed representations of word meaning. Common tasks in lexical semantics such as word relatedness or selectional preference can benefit from modeling such structure: Polysemous word usage is often governed by some common background metaphoric usage (e.g. the senses of line or run), and likewise modeling the selectional preference of verbs relies on identifying commonalities shared by their typical arguments. Tiered clustering can also be viewed as a form of soft feature selection, where features that do not contribute meaningfully to the clustering can be excluded. We demonstrate the applicability of tiered clustering, highlighting particular cases where modeling shared structure is beneficial and where it can be detrimental.