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CICLING
2011
Springer

Ranking Multilingual Documents Using Minimal Language Dependent Resources

8 years 2 months ago
Ranking Multilingual Documents Using Minimal Language Dependent Resources
This paper proposes an approach of extracting simple and effective features that enhances multilingual document ranking (MLDR). There is limited prior research on capturing the concept of multilingual document similarity in determining the ranking of documents. However, the literature available has worked heavily with language specific tools, making them hard to reimplement for other languages. Our approach extracts various multilingual and monolingual similarity features using a basic language resource (bilingual dictionary). No language-specific tools are used, hence making this approach extensible for other languages. We used the datasets provided by Forum for Information Retrieval Evaluation (FIRE) 1 for their 2010 Adhoc Cross-Lingual document retrieval task on Indian languages. Experiments have been performed with different ranking algorithms and their results are compared. The results obtained showcase the effectiveness of the features considered in enhancing multilingual doc...
G. S. K. Santosh, N. Kiran Kumar, Vasudeva Varma
Added 25 Aug 2011
Updated 25 Aug 2011
Type Journal
Year 2011
Where CICLING
Authors G. S. K. Santosh, N. Kiran Kumar, Vasudeva Varma
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