Document (#34942)

Author

Ahmed, F.
Nürnberger, A.

Title

Evaluation of n-gram conflation approaches for Arabic text retrieval

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.7, S.1448-1465

Year

2009

Abstract

In this paper we present a language-independent approach for conflation that does not depend on predefined rules or prior knowledge of the target language. The proposed unsupervised method is based on an enhancement of the pure n-gram model that can group related words based on various string-similarity measures, while restricting the search to specific locations of the target word by taking into account the order of n-grams. We show that the method is effective to achieve high score similarities for all word-form variations and reduces the ambiguity, i.e., obtains a higher precision and recall, compared to pure n-gram-based approaches for English, Portuguese, and Arabic. The proposed method is especially suited for conflation approaches in Arabic, since Arabic is a highly inflectional language. Therefore, we present in addition an adaptive user interface for Arabic text retrieval called araSearch. araSearch serves as a metasearch interface to existing search engines. The system is able to extend a query using the proposed conflation approach such that additional results for relevant subwords can be found automatically.

Theme

Computerlinguistik

Object

n-grams

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5. Aljlayl, M.; Frieder, O.; Grossman, D.: On bidirectional English-Arabic search (2002) 0.19

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