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Using relevance feedback and ranking in interactive searching

Nicholas J. Belkin, Colleen Cool, Jürgen Koenemann, Kwong Bor Ng, Soyeon Park

Open publisher page 33 citations

Abstract

We present results of a study in which 50 searchers, of varying degrees of experience in information retrieval (IR), each performed searches on two TREC-4 adhoc interactive track topics, using a simple interface to the INQUIRY retrieval engine. The foci of our study were : the relationships between the users'models and experience of IR, and their performance in the TREC-4 adhoc task while using a best-match IR system with relevance feedback ; the understanding, use and utility of relevance feedback and ranking in interactive IR ; and, the evaluation of interactive IR.

About this research paper

What this paper is about

We present results of a study in which 50 searchers, of varying degrees of experience in information retrieval (IR), each performed searches on two TREC-4 adhoc interactive track topics, using a simple interface to the INQUIRY retrieval engine. The foci of our study were : the relationships between the users'models and experience of IR, and their performance in the TREC-4 adhoc task while using a best-match IR system with relevance feedback ; the understanding, use and utility of relevance feedback and ranking in interactive IR ; and, the evaluation of interactive IR.

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OpenAlex reports 33 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

We present results of a study in which 50 searchers, of varying degrees of experience in information retrieval (IR), each performed searches on two TREC-4 adhoc interactive track topics, using a simple interface to the INQUIRY retrieval engine. The foci of our study were : the relationships between the users'models and experience of IR, and their performance in the TREC-4 adhoc task while using a best-match IR system with relevance feedback ; the understanding, use and utility of relevance feedback and ranking in interactive IR ; and, the evaluation of interactive IR.

Key concepts: Ranking (information retrieval), Relevance feedback, Relevance (law), Computer science, Information retrieval, Task (project management), Interface (matter), Search engine

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