Evaluating query-independent object features for relevancy prediction

Authors:
Andres R. Masegosa;Hideo Joho;Joemon M. Jose
Affiliations:
Department of Computer Science and A.I., University of Granada, Spain;Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK
Venue:
ECIR'07 Proceedings of the 29th European conference on IR research
Year:
2007

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Abstract

This paper presents a series of experiments investigating the effectiveness of query-independent features extracted from retrieved objects to predict relevancy. Features were grouped into a set of conceptual categories, and individually evaluated based on click-through data collected in a laboratory-setting user study. The results showed that while textual and visual features were useful for relevancy prediction in a topic-independent condition, a range of features can be effective when topic knowledge was available. We also re-visited the original study from the perspective of significant features identified by our experiments.