Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic construction of multifaceted browsing interfaces
Proceedings of the 14th ACM international conference on Information and knowledge management
Towards effective browsing of large scale social annotations
Proceedings of the 16th international conference on World Wide Web
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
A method for learning part-whole relations
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Journal of the American Society for Information Science and Technology
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Manually constructed thesauri are not updated regularly, so they are hard to catch the fast emergence of new words. Moreover, the vocabularies of the professionals who construct the thesauri may not completely match the vocabularies of normal users. Recently, Folksonomy services are very popular and highly sensitive to information drift and the change of users' vocabularies. In this paper, we explore a method for enriching formal thesauri with informal Folksonomies. We demonstrate our method by semi-automatically enriching WordNet with new words emerging from a social bookmark service. Tags are related to each other by the subsumption relationships extracted from Folksonomies. New words are recommended to be placed in appropriate synsets of the WordNet hierarchy. An initial evaluation on our experimental result shows the effectiveness of our method.