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Information retrieval (IR) systems are traditionally developed using the objective relevance approach based on the “best match” principle assuming that users can specify their needs in queries and that the documents retrieved are relevant to them. This paper advocates a subjective relevance (SR) approach to value-add objective relevance and address its limitations by considering relevance in terms of users' needs and contexts. A pilot study was conducted to elicit features on SR from experts and novices. Elicited features were then analyzed using characteristics of SR types and stages in information seeking to inform the design of an IR interface supporting SR. The paper presents initial work towards the design and development of user-centered IR systems that prompt features supporting the four main types of SR.