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A graph-based approach to mining multilingual word associations from wikipedia
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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval table of contents
Boston, MA, USA
POSTER SESSION: Posters table of contents
Pages 690-691  
Year of Publication: 2009
ISBN:978-1-60558-483-6
Authors
Zheng Ye  York University , Toronto, ON, Canada
Xiangji Huang  York University , Toronto, ON, Canada
Hongfei Lin  Dalian University of Technology , Dalian, China
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we propose a graph-based approach to constructing a multilingual association dictionary from Wikipedia, in which we exploit two kinds of links in Wikipedia articles to associate multilingual words and concepts together in a graph. The mined association dictionary is applied in cross language information retrieval (CLIR) to verify its quality. We evaluate our approach on four CLIR data sets and the experimental results show that it is possible to mine a good multilingual association dictionary from Wikipedia articles.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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E. Gabrilovich and S. Markovitch. Computing semantic relatedness using wikipedia-based explicit semantic analysis. In Proc. of IJCAI'07, pp 1606--1611.
 
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Collaborative Colleagues:
Zheng Ye: colleagues
Xiangji Huang: colleagues
Hongfei Lin: colleagues