Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
A vector space model for automatic indexing
Communications of the ACM
Experiments with LSA scoring: optimal rank and basis
Computational information retrieval
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Applied morphological processing of English
Natural Language Engineering
Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
CorMet: a computational, corpus-based conventional metaphor extraction system
Computational Linguistics
Syntactic features and word similarity for supervised metonymy resolution
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Metaphor-based meaning excavation
Information Sciences: an International Journal
Active learning for the identification of nonliteral language
FigLanguages '07 Proceedings of the Workshop on Computational Approaches to Figurative Language
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
Query difficulty prediction for contextual image retrieval
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Economically organized hierarchies in WordNet and the Oxford English Dictionary
Cognitive Systems Research
Proactive screening for depression through metaphorical and automatic text analysis
Artificial Intelligence in Medicine
Regular polysemy: a distributional model
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
Distributional semantics in technicolor
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Fast large-scale approximate graph construction for NLP
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Evaluating the premises and results of four metaphor identification systems
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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Metaphor is ubiquitous in text, even in highly technical text. Correct inference about textual entailment requires computers to distinguish the literal and metaphorical senses of a word. Past work has treated this problem as a classical word sense disambiguation task. In this paper, we take a new approach, based on research in cognitive linguistics that views metaphor as a method for transferring knowledge from a familiar, well-understood, or concrete domain to an unfamiliar, less understood, or more abstract domain. This view leads to the hypothesis that metaphorical word usage is correlated with the degree of abstractness of the word's context. We introduce an algorithm that uses this hypothesis to classify a word sense in a given context as either literal (denotative) or metaphorical (connotative). We evaluate this algorithm with a set of adjective-noun phrases (e.g., in dark comedy, the adjective dark is used metaphorically; in dark hair, it is used literally) and with the TroFi (Trope Finder) Example Base of literal and nonliteral usage for fifty verbs. We achieve state-of-the-art performance on both datasets.