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In recent years, user\u2010oriented Information Seeking (IS) research methods rooted in the social sciences have been integrated with Information Retrieval (IR) research approaches based on computer science to capitalize on the strengths of each field. Given this background, the objective is to develop a topic\u2010needs variation determination technique based on the observations of IS&amp;R theories.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>In this study, implicit and explicit methods for identifying users' evolving topic\u2010needs are proposed. Knowledge\u2010intensive tasks performed by academic researchers are used to evaluate the efficacy of the proposed methods. The paper conducted two sets of experiments to demonstrate and verify the importance of determining changes in topic\u2010needs during the IS&amp;R process.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The results in terms of precision and discounted cumulated gain (DCG) values show that the proposed Stage\u2010Topic_W (G,S) and Stage\u2010Topic\u2010Interaction methods can retrieve relevant document sets for users engaged in long\u2010term tasks more efficiently and effectively than traditional methods.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The improved precision of the proposed methods means that they can retrieve more relevant documents for the searcher. Accordingly, the results of this research have implications for enhancing the search function in enterprise content management (ECM) applications to support the execution of projects\/tasks by professionals and facilitate effective ECM.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The model observes a user's search behavior pattern to determine the personal factors (e.g. changes in the user's cognitive status), and content factors (e.g. changes in topic\u2010needs) simultaneously. The objective is to capture changes in the user's information needs precisely so that evolving information needs can be satisfied in a timely manner.<\/jats:p><\/jats:sec>","DOI":"10.1108\/00220411111124578","type":"journal-article","created":{"date-parts":[[2011,5,21]],"date-time":"2011-05-21T07:04:22Z","timestamp":1305961462000},"page":"525-561","source":"Crossref","is-referenced-by-count":11,"title":["Toward supporting information\u2010seeking and retrieval activities based on evolving topic\u2010needs"],"prefix":"10.1108","volume":"67","author":[{"given":"I\u2010Chin","family":"Wu","sequence":"first","affiliation":[]}],"member":"140","reference":[{"key":"key2022013020390622500_b1","unstructured":"Baeza\u2010Yates, R. and Ribeiro\u2010Neto, B. (1999), Modern Information Retrieval, Addison\u2010Wesley Longman, Boston, MA."},{"key":"key2022013020390622500_b2","doi-asserted-by":"crossref","unstructured":"Balabanovic, M. and Shoham, Y. 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