WordNet: a lexical database for English
Communications of the ACM
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Automatic assignment of wikipedia encyclopedic entries to wordnet synsets
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
Towards Ontology Use, Re-use and Abuse in a Computational Creativity CollectiveA Position Statement
Proceedings of the 2010 conference on Modular Ontologies: Proceedings of the Fourth International Workshop (WoMO 2010)
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Most new words, or neologisms, bubble beneath the surface of widespread usage for some time, perhaps even years, before gaining acceptance in conventional print dictionaries [1]. A shorter, yet still significant, delay is also evident in the life-cycle of NLP-oriented lexical resources like WordNet [2]. A more topical lexical resource is Wikipedia [3], an open-source community-maintained encyclopedia whose headwords reflect the many new words that gain recognition in a particular linguistic sub-culture. In this paper we describe the principles behind Zeitgeist, a system for dynamic lexicon growth that harvests and semantically analyses new lexical forms from Wikipedia, to automatically enrich WordNet as these new word forms are minted. Zeitgeist demonstrates good results for composite words that exhibit a complex morphemic structure, such as portmanteau words and formal blends [4, 5].