IR of XML Documents – A Collective Ranking Strategy
Author(s) -
Maha Salem,
Alan Woodley,
Shlomo Geva
Publication year - 2005
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-26166-4
DOI - 10.1007/11424550_10
Subject(s) - ranking (information retrieval) , computer science , information retrieval , xml , search engine , human–computer information retrieval , adversarial information retrieval , world wide web , cognitive models of information retrieval
Within the area of Information Retrieval (IR) the importance of appropriate\udranking of results has increased markedly. The importance is magnified\udin the case of systems dedicated to XML retrieval, since users of these systems\udexpect the retrieval of highly relevant and highly precise components, instead\udof the retrieval of entire documents. As an international, coordinated effort\udto evaluate the performance of Information Retrieval systems, the Initiative\udfor the Evaluation of XML Retrieval (INEX) encourages participating organisation\udto run queries on their search engines and to submit their result for the annual\udINEX workshop. In previous INEX workshops the submitted results were\udmanually assessed by participants and the search engines were ranked in terms\udof performance. This paper presents a Collective Ranking Strategy that outperforms\udall search engines it is based on. Moreover it provides a system that is\udtrying to facilitate the ranking of participating search engines
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