Purpose: Seeking and retrieving information is an essential aspect of knowledge workers' activities during problem-solving and decision-making tasks. In recent years, user-oriented 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-needs variation determination technique based on the observations of IS&R theories. Design/methodology/approach: In this study, implicit and explicit methods for identifying users' evolving topic-needs are proposed. Knowledge-intensive 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-needs during the IS&R process. Findings: The results in terms of precision and discounted cumulated gain (DCG) values show that the proposed Stage-Topic_W (G,S) and Stage-Topic-Interaction methods can retrieve relevant document sets for users engaged in long-term tasks more efficiently and effectively than traditional methods. Practical implications: 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. Originality/value: 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-needs) 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.
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