Abstract
An adaptive interface autonomously adjusts its display and available actions to current goals and abilities of the user by assessing user status, system task, and the context. Knowledge content adaptability is needed for knowledge acquisition and refinement tasks. In the case of knowledge content adaptability, the requirements of interface design focus on the elicitation of information from the user and the refinement of information based on patterns of interaction. In such cases, the emphasis on adaptability is on facilitating information search and knowledge discovery. In this article, we present research on adaptive interfaces that facilitates personalized information seeking from a large data warehouse. The resulting proof-of-concept system, called source recommendation system (SRS), assists users in locating and navigating data sources in the repository. Based on the initial user query and an analysis of the content of the search results, the SRS system generates a profile of the user tailored to the individual's context during information seeking. The user profiles are refined successively and are used in progressively guiding the user to the appropriate set of sources within the knowledge base. The SRS system is implemented as an Internet browser plug-in to provide a seamless and unobtrusive, personalized experience to the users during the information search process. The rationale behind our approach, system design, empirical evaluation, and implications for research on adaptive interfaces are described in this paper.
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