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Abstract : |
Abstract. In this paper we examine the growing interest in personalized user interfaces and explore the potential of machine learning in meeting that need. We briefly review progress in developing fielded applications of machine learning, then consider some characteristics of adaptive user interfaces that distinguish them from more traditional applications. After this, we consider some examples of adaptive interfaces that use inductive methods to personalize their behavior, and we report some ongoing research that extends these ideas in the automobile environment. 1 The Need for Personalized User Interfaces Early computer software aimed to solve business and scientific problems in a predetermined way that allowed only very constrained user input, through arguments given to the program at run time. This contrasts sharply with modernday software, which is much more interactive and supports frequent user input throughout its operation. This shift toward interactive software is reflected in the growing emphasis on interfaces designed to ease communication between, |
