Promoting Document Relevance Using Query Term Proximity for Exploratory Search

Vikram Singh

International Journal of Information Retrieval Research (IJIRR), 2023, vol. 13, issue 1, 1-22

Abstract: In the information retrieval system, relevance manifestation is pivotal and regularly based on document-term statistics, i.e., term frequency (tf), inverse document frequency (idf), etc. Query term proximity (QTP) within matched documents is mostly under-explored. In this article, a novel information retrieval framework is proposed to promote the documents among all relevant retrieved ones. The relevance estimation is a weighted combination of document statistics and query term statistics, and term-term proximity is simply aggregates of diverse user preferences aspects in query formation, thus adapted into the framework with conventional relevance measures. Intuitively, QTP is exploited to promote the documents for balanced exploitation-exploration, and eventually navigate a search towards goals. The evaluation asserts the usability of QTP measures to balance several seeking tradeoffs, e.g., relevance, novelty, result diversification (coverage, topicality), and overall retrieval. The assessment of user search trails indicates significant growth in a learning outcome (due to novelty).

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:13:y:2023:i:1:p:1-22

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