The Analysis of Rank Fusion Techniques to Improve Query Relevance
Abstract: Rank fusion
meta-search engine algorithms can be used to merge web search results of
multiple search engines. In this paper we introduce two variants of the
Weighted Borda-Fuse algorithm. The first variant retrieves documents based on
popularities of component engines. The second one is based on k user-defined
toplist of component engines. In this research, experiments were performed on
k={50,100,200} toplist with AND/OR combinations implemented on ‘UNIB Meta
Fusion’ meta-search engine prototype which employed 3 out of 5 popular search
engines. Both of our two algorithms outperformed other rank fusion algorithms
(relevance score is upto 0.76 compare to Google that is 0.27, at P@10). The
pseudo-relevance automatic judgement techniques involved are Reciprocal Rank,
Borda Count, and Condorcet. The optimal setting was reached for queries with
operator "AND" (degree 1) or "AND ... AND" (degree 2) with
k=200. The ‘UNIB Meta Fusion’ meta-search engine system was built correctly.
Keywords: Weighted Borda-Fuse,
rank fusion, meta-search engine, pseudo-relevance automatic judgement, query
relevance
Author: Diyah Puspitaningrum,
Jeri Apriansyah Pagua, Aan Erlansari, Fauzi Fauzi, Rusdi Efendi, Desi
Andreswari, I.S.W.B. Prasetya
Journal Code: jptkomputergg150181
