Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information

Michael Roth, Sabine Schulte im Walde

Abstract
Distributional, corpus-based descriptions have frequently been applied to model aspects of word meaning. However, distributional models that use corpus data as their basis have one well-known disadvantage: even though the distributional features based on corpus co-occurrence were often successful in capturing meaning aspects of the words to be described, they generally fail to capture those meaning aspects that refer to world knowledge, because coherent texts tend not to provide redundant information that is presumably available knowledge. The question we ask in this paper is whether dictionary and encyclopaedic resources might complement the distributional information in corpus data, and provide world knowledge that is missing in corpora. As test case for meaning aspects, we rely on a collection of semantic associates to German verbs and nouns. Our results indicate that a combination of the knowledge resources should be helpful in work on distributional descriptions.
Anthology ID:
L08-1163
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/473_paper.pdf
DOI:
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Cite (ACL):
Michael Roth and Sabine Schulte im Walde. 2008. Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information (Roth & Schulte im Walde, LREC 2008)
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http://www.lrec-conf.org/proceedings/lrec2008/pdf/473_paper.pdf
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