EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
Learning dictionaries for information extraction by multi-level bootstrapping
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
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
Acquisition of categorized named entities for web search
Proceedings of the thirteenth ACM international conference on Information and knowledge management
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
A graph model for unsupervised lexical acquisition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Unsupervised named-entity extraction from the web: an experimental study
Artificial Intelligence
Exploiting strong syntactic heuristics and co-training to learn semantic lexicons
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Fine-grained proper noun ontologies for question answering
SEMANET '02 Proceedings of the 2002 workshop on Building and using semantic networks - Volume 11
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Towards terascale knowledge acquisition
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Weakly-supervised discovery of named entities using web search queries
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Automatically generating extraction patterns from untagged text
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Not all seeds are equal: measuring the quality of text mining seeds
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Learning arguments and supertypes of semantic relations using recursive patterns
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Towards semantic category verification with arbitrary precision
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
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Various techniques have been developed to automatically induce semantic dictionaries from text corpora and from the Web. Our research combines corpus-based semantic lexicon induction with statistics acquired from the Web to improve the accuracy of automatically acquired domain-specific dictionaries. We use a weakly supervised bootstrapping algorithm to induce a semantic lexicon from a text corpus, and then issue Web queries to generate co-occurrence statistics between each lexicon entry and semantically related terms. The Web statistics provide a source of independent evidence to confirm, or disconfirm, that a word belongs to the intended semantic category. We evaluate this approach on 7 semantic categories representing two domains. Our results show that the Web statistics dramatically improve the ranking of lexicon entries, and can also be used to filter incorrect entries.