Word association norms, mutual information, and lexicography
Computational Linguistics
Experiment on linguistically-based term associations
Information Processing and Management: an International Journal
Similarity-based approaches to natural language processing
Similarity-based approaches to natural language processing
Similarity-Based Models of Word Cooccurrence Probabilities
Machine Learning - Special issue on natural language learning
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Discovery of inference rules for question-answering
Natural Language Engineering
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Principle-based parsing without overgeneration
ACL '93 Proceedings of the 31st 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
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Extracting paraphrases from a parallel corpus
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
A general framework for distributional similarity
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity
Computational Linguistics
The distributional inclusion hypotheses and lexical entailment
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Integrating pattern-based and distributional similarity methods for lexical entailment acquisition
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A supervised learning approach to automatic synonym identification based on distributional features
HLT-SRWS '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Evaluating the inferential utility of lexical-semantic resources
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Finding word substitutions using a distributional similarity baseline and immediate context overlap
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Bootstrapping distributional feature vector quality
Computational Linguistics
Graph-based clustering for semantic classification of onomatopoetic words
TextGraphs-3 Proceedings of the 3rd Textgraphs Workshop on Graph-Based Algorithms for Natural Language Processing
The distributional similarity of sub-parses
EMSEE '05 Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment
Discriminative training of clustering functions: theory and experiments with entity identification
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
A lexical alignment model for probabilistic textual entailment
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
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We suggest a new goal and evaluation criterion for word similarity measures. The new criterion - meaning-entailing substitutability - fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level of human agreement. Motivated by this semantic criterion we analyze the empirical quality of distributional word feature vectors and its impact on word similarity results, proposing an objective measure for evaluating feature vector quality. Finally, a novel feature weighting and selection function is presented, which yields superior feature vectors and better word similarity performance.