The Journal of Machine Learning Research
Using a probabilistic class-based lexicon for lexical ambiguity resolution
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
More accurate tests for the statistical significance of result differences
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Language models based on semantic composition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
A latent dirichlet allocation method for selectional preferences
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Latent variable models of selectional preference
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Compositional matrix-space models of language
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Topic models for word sense disambiguation and token-based idiom detection
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
A regression model of adjective-noun compositionality in distributional semantics
GEMS '10 Proceedings of the 2010 Workshop on GEometrical Models of Natural Language Semantics
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A structured vector space model for hidden attribute meaning in adjective-noun phrases
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Distributional memory: A general framework for corpus-based semantics
Computational Linguistics
GEMS '11 Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics
GEMS '11 Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics
Domain adaptation of a dependency parser with a class-class selectional preference model
ACL '12 Proceedings of ACL 2012 Student Research Workshop
Finding additional semantic entity information for search engines
Proceedings of the Seventeenth Australasian Document Computing Symposium
Discovering coherent topics using general knowledge
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
WebChild: harvesting and organizing commonsense knowledge from the web
Proceedings of the 7th ACM international conference on Web search and data mining
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This paper introduces an attribute selection task as a way to characterize the inherent meaning of property-denoting adjectives in adjective-noun phrases, such as e.g. hot in hot summer denoting the attribute temperature, rather than taste. We formulate this task in a vector space model that represents adjectives and nouns as vectors in a semantic space defined over possible attributes. The vectors incorporate latent semantic information obtained from two variants of LDA topic models. Our LDA models outperform previous approaches on a small set of 10 attributes with considerable gains on sparse representations, which highlights the strong smoothing power of LDA models. For the first time, we extend the attribute selection task to a new data set with more than 200 classes. We observe that large-scale attribute selection is a hard problem, but a subset of attributes performs robustly on the large scale as well. Again, the LDA models outperform the VSM baseline.