ComRank: Metasearch and Automatic Ranking of XML Retrieval Systems
Woodley, Alan P. & Geva, Shlomo (2005) ComRank: Metasearch and Automatic Ranking of XML Retrieval Systems. In Kunii, Toysiyasu L., Hock Soon, Seah, & Sourin, Alexi (Eds.) International Conference on Cyberworlds, 23-25 November 2005, Singapore.
Different information retrieval (IR) systems often return very diverse results lists for the same query. This is problematic for users since no one IR system works best for every scenario, and it is difficult for the user to know which system will work best a priori. The challenge of metasearch is to merge results lists from several IR systems, with the goal of outperforming each of the constituent systems. This paper presents ComRank, a metasearch system that discriminates in favour of results that (1) originate by consensus amongst several systems; (2) are highly ranked in their original systems and (3) originate from the better performing systems. Importantly, ComRank determines the ‘better’ performing systems without the need for human judgements. Rather, it uses an automatic assessment process that ranks systems by their pseudo-relevance, as derived from highly ranked results in ComRank’s list. We apply our methods to the INEX Collection, which is an unexplored domain for these methods, and show that they are comparable to or better than baseline alternatives.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||XML, Informtaion Retrieval, Metasearch Engines, Rank Algorithms|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2005 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||23 Mar 2006 00:00|
|Last Modified:||29 Feb 2012 13:15|
Repository Staff Only: item control page