New Re-ranking Approach in Merging Search Results

Authors

  • Hung Trung Vo The University of Danang

DOI:

https://doi.org/10.31449/inf.v43i2.2132

Abstract

When merging query results from various information sources or from different search engines, popular methods based on available documents scores or on order ranks in returned lists, its can ensure the fast response, but results are often inconsistent. Another approach is downloading contents of top documents for re-indexing and re-ranking to create final ranked result list. This method guarantees better quality but is resource-consuming. In this paper, we compare two methods of merging search results: a) applying formulas to re-evaluate document based on different combinations of returned order ranks, documents titles and snippets; b) Top-Down Re-ranking algorithm (TDR) gradually downloads, calculates scores and adds top documents from each source into the final list. We propose also a new way to re-rank search results based on genetic programming and re-ranking learning. Experimental result shows that the proposed method is better than traditional methods in terms of both quality and time.

Author Biography

Hung Trung Vo, The University of Danang

Prof. VO Trung Hung is a Senior Lecturer at the Faculty of Information Technology, the University of Danang. He graduated Ph.D. in Computer Science at Grenoble National Institute of Technology (French) in 2004. Having taught and held positions as Deputy Dean of Information Technology Faculty (University of Sciences and Technology) period 2005-2006; Head of the Department of Science - Postgraduate and International Cooperation of University of Sciences and Technology 2006-2010; Head of the Department of Science and Technology of the University of Danang and Director of Software Development Center from 2010 to present. He has been involved in management of many international organizations and projects such as Technical University's Coordinator Association (AUF), Coordinator of MekongSkill2Work (USAID), Coordinator of international projects such as HUB4Growth, HR4Asia, EMMAsia (European Commission). His interest research iss included Natural Language Processing, Software Engineering, and Artificial Intelligence.

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Published

2019-06-15

How to Cite

Vo, H. T. (2019). New Re-ranking Approach in Merging Search Results. Informatica, 43(2). https://doi.org/10.31449/inf.v43i2.2132

Issue

Vol. 43 No. 2 (2019)

Section

Regular papers

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