MarQO: A query optimizer in multilingual environment for information retrieval in Marathi language

Suhas D. Pachpande 1, * and Parag U. Bhalchandra 2

1 Department of Computer Science, Sant Gadge Baba Amravati University, Amravati, India.
2 School of Computational Sciences, S.R.T.M. University, Nanded, India.
 
Research Article
International Journal of Science and Research Archive, 2023, 09(02), 986–996.
Article DOI: 10.30574/ijsra.2023.9.2.0712
Publication history: 
Received on 15 July 2023; revised on 24 August 2023; accepted on 27 August 2023
 
Abstract: 
Information retrieval is a crucial component of modern information systems. A significant portion of the vast amount of information stored worldwide is in local languages. While most information retrieval systems are designed primarily for English, there is a growing need for these systems to work with data in languages other than English. Cross Language Information Retrieval (CLIR) systems play a pivotal role in enabling information retrieval across multiple languages. However, these systems often face challenges due to ambiguities in query translation, impacting retrieval accuracy. This paper introduces "MarQO," a query optimizer designed to address these challenges in the context of Marathi language. MarQO employs a multi-stage approach, including lexical processing, extraction of multi-word terms, synonym addition, phrasal translations, utilization of word co-occurrence statistics, and more. By disambiguating query keyword translations, MarQO significantly improves the accuracy of translations, thereby leading to more relevant document retrieval results.
 
Keywords: 
Cross Language Information Retrieval; Multi-word terms; Phrasal translation
 
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