This paper explores refinements to methods used in a procedure being developed by the authors to personalize user interfaces for online shopping support tools. In the authors ’ original procedure, classical methods in rough set theory are used in conjunction with traditional algorithms in web usage mining. This paper will explore an alternative approach, specifically the dominance-based rough set approach (DRSA), for use with the authors ’ original procedure. DRSA has its foundations in the classical rough set approach (CRSA). However unlike CRSA, DRSA considers feature/preference-ordered data. In web usage mining analyses, where elicitation of user preferences is a common task, feature/preference order is an important factor and may provide insights that classical/traditional approaches may omit. The authors discuss how DRSA may benefit and improve their original procedure and discuss how the information gained from DRSA analyses could be used to further build their original procedure by enabling item ordering and feature highlighting. This paper will describe the research process, outcomes, and outline opportunities for future work.
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