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A Topic Modeling Based Approach for Enhancing Corpus Querying

A Topic Modeling Based Approach for Enhancing Corpus Querying

Nouh Talal Alhindawi, Belal Abu Ata, Lana Mahmoud Obeidat, Mohammad Subhi Al-Batah, Muad Abu-Ata
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 13
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781522565543|DOI: 10.4018/IJOSSP.2019070103
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MLA

Alhindawi, Nouh Talal, et al. "A Topic Modeling Based Approach for Enhancing Corpus Querying." IJOSSP vol.10, no.3 2019: pp.38-50. http://doi.org/10.4018/IJOSSP.2019070103

APA

Alhindawi, N. T., Abu Ata, B., Obeidat, L. M., Al-Batah, M. S., & Abu-Ata, M. (2019). A Topic Modeling Based Approach for Enhancing Corpus Querying. International Journal of Open Source Software and Processes (IJOSSP), 10(3), 38-50. http://doi.org/10.4018/IJOSSP.2019070103

Chicago

Alhindawi, Nouh Talal, et al. "A Topic Modeling Based Approach for Enhancing Corpus Querying," International Journal of Open Source Software and Processes (IJOSSP) 10, no.3: 38-50. http://doi.org/10.4018/IJOSSP.2019070103

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Abstract

In information retrieval, the accuracy of the retrieval process is mainly dependent on query terms selection; therefore, the user must choose the needed terms carefully and selectively. Traditionally, the process of selecting query terms is done manually. However, in the last two decades, a lot of research has been directed towards automating the process of choosing and enhancing query terms. In this article, a new novel approach is presented, which relies on topic modeling in query building and expansion. Two open source systems were selected to perform the experiments, results show that adding the topic's term to the user's query clearly improves its quality and thus, improves the ranking results.

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