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• W2959888955 abstract "Modern information systems are expected to assist users with diverse goals, via exploiting the topical dimension (‘what' the user is searching for) of information needs. However, the intent dimension (‘why' the user is searching) has preferred relatively lesser for the same intention. Traditionally, the intent is an ‘immediate reason, purpose, or goal' that motivates the user search, and captured in search contexts (Pre-search, In-search, Pro-Search), an ideal information system would be able to use. This article proposes a novel intent estimation strategy; based on the intuition that captured intent, and proactively extracts likely results. The captured ‘Pre-search' context adapts query term proximities within matched results beside document-term statistics and pseudo-relevance feedback with user-relevance feedback for In-search. The assessment asserts the superior performance of the proposed strategy over the equivalent on tradeoffs, e.g., novelty, diversity (coverage, topicality), retrieval (precision, recall, F-measure) and exploitation vs exploration." @default.
• W2959888955 created "2019-07-23" @default.
• W2959888955 creator A5027196381 @default.
• W2959888955 date "2019-07-01" @default.
• W2959888955 modified "2023-09-27" @default.
• W2959888955 title "Predicting Search Intent Based on In-Search Context for Exploratory Search" @default.
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• W2959888955 doi "https://doi.org/10.4018/ijapuc.2019070104" @default.
• W2959888955 hasPublicationYear "2019" @default.
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