Using PageRank to infer user preferences

Authors:
Praveen Chandar;Ben Carterette
Affiliations:
University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA
Venue:
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Year:
2012

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Abstract

Recently, researchers have shown interest in the use of preference judgments for evaluation in IR literature. Although preference judgments have several advantages over absolute judgment, one of the major disadvantages is that the number of judgments needed increases polynomially as the number of documents in the pool increases. We propose a novel method using PageRank to minimize the number of judgments required to evaluate systems using preference judgments. We test the proposed hypotheses using the TREC 2004 to 2006 Terabyte dataset to show that it is possible to reduce the evaluation cost considerably. Further, we study the susceptibility of the methods due to assessor errors.