Class-based n-gram models of natural language
Computational Linguistics
Open-domain textual question answering techniques
Natural Language Engineering
Hybrid Neural Document Clustering Using Guided Self-Organization and WordNet
IEEE Intelligent Systems
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Finding parts in very large corpora
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Learning semantic constraints for the automatic discovery of part-whole relations
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
The distributional inclusion hypotheses and lexical entailment
ACL '05 Proceedings of the 43rd Annual Meeting on 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
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
A metric-based framework for automatic taxonomy induction
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Learning arguments and supertypes of semantic relations using recursive patterns
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Word sense induction & disambiguation using hierarchical random graphs
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A graph-based algorithm for inducing lexical taxonomies from scratch
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
MaxMax: a graph-based soft clustering algorithm applied to word sense induction
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
A hierarchical Dirichlet model for taxonomy expansion for search engines
Proceedings of the 23rd international conference on World wide web
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This paper presents a novel approach for inducing lexical taxonomies automatically from text. We recast the learning problem as that of inferring a hierarchy from a graph whose nodes represent taxonomic terms and edges their degree of relatedness. Our model takes this graph representation as input and fits a taxonomy to it via combination of a maximum likelihood approach with a Monte Carlo Sampling algorithm. Essentially, the method works by sampling hierarchical structures with probability proportional to the likelihood with which they produce the input graph. We use our model to infer a taxonomy over 541 nouns and show that it outperforms popular flat and hierarchical clustering algorithms.