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This article proposes a novel intent estimation strategy; based on the intuition that captured intent, and proactively extracts likely results. The captured \u2018Pre-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.<\/jats:p>","DOI":"10.4018\/ijapuc.2019070104","type":"journal-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T16:29:13Z","timestamp":1562776153000},"page":"53-75","source":"Crossref","is-referenced-by-count":3,"title":["Predicting Search Intent Based on In-Search Context for Exploratory Search"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6315-0872","authenticated-orcid":true,"given":"Vikram","family":"Singh","sequence":"first","affiliation":[{"name":"National Institute of Technology, Kurukshetra, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJAPUC.2019070104-0","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-4571(199404)45:3<149::AID-ASI5>3.0.CO;2-J"},{"key":"IJAPUC.2019070104-1","doi-asserted-by":"crossref","unstructured":"Bates, M. 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