Improving Cross Language Information Retrieval Using Corpus Based Query Suggestion Approach

  • Rajendra PrasathEmail author
  • Sudeshna Sarkar
  • Philip O’Reilly
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9042)


Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the another language. We use FIRE corpora - Tamil and English news collections - in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach.


Query Suggestion Corpus Statistics Cross-Lingual Document Retrieval Retrieval Efficiency 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Rajendra Prasath
    • 1
    • 2
    Email author
  • Sudeshna Sarkar
    • 1
  • Philip O’Reilly
    • 2
  1. 1.Department of Computer Science and EngineeringIndian Institute of TechnologyKharagpurIndia
  2. 2.Dept of Business Information SystemsUniversity College CorkCorkIreland

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