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  A Machine Learning Approach to Building Aligned Wordnets

de Melo, G., & Weikum, G. (2008). A Machine Learning Approach to Building Aligned Wordnets. In Proceedings of the First International Conference on Global Interoperability for Language Resources (pp. 163-170). Hong Kong: Department of Chinese, Translation and Linguistics, City University of Hong Kong.

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 Creators:
de Melo, Gerard1, Author           
Weikum, Gerhard1, Author           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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 Abstract: WordNet is a lexical database describing English words and their senses. We propose a method for automatically producing similar resources for new languages by taking advantage of the original WordNet in conjunction with translation dictionaries. A small set of training mappings is used to learn a model for predicting associations between terms and senses. The associations are represented using a variety of scores that take into account structural properties as well as semantic relatedness and corpus frequency information. For evaluation, we created a German-language wordnet, and the data indicate a significantly better coverage and higher precision than previous heuristics. The resulting resources provide not only valuable information for monolingual NLP tasks but also enable a high degree of cross-lingual interoperability.

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Language(s): eng - English
 Dates: 2009-03-312008
 Publication Status: Issued
 Pages: -
 Publishing info: Hong Kong : Department of Chinese, Translation and Linguistics, City University of Hong Kong
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 428270
URI: http://icgl.ctl.cityu.edu.hk/2008/html/resources/~proceeding_conference.pdf
Other: Local-ID: C125756E0038A185-583777D81F9CD012C1257418004D71A3-deMeloWeikum2008b
 Degree: -

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Title: Untitled Event
Place of Event: Hong Kong
Start-/End Date: 2008-01-08 - 2008-01-12

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Title: Proceedings of the First International Conference on Global Interoperability for Language Resources
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Hong Kong : Department of Chinese, Translation and Linguistics, City University of Hong Kong
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 163 - 170 Identifier: -