Adaptive User Interfaces for Personalized Services
Author(s)
Langley, Pat
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Abstract
The Internet has made available massive amounts of information and given users more choices than ever before, but all too often the result is more confusion than satisfaction. Intelligent assistants can help people filter relevant information and guide their choices, but users have different goals and distinctive tastes. In this talk, I report work adaptive user interfaces -- interactive systems that automatically personalize their content to individual users. These incorporate technology and principles from machine learning, intelligent agents, and human-computer interaction to improve the user's experience. I describe a number of prototype systems, including a personalized navigation aide, an adaptive news reader, and a conversational destination advisor. Along the way, I consider design decisions about the problem formulation, the representation of user profiles, the unobtrusive collection of user feedback, and the effective utilization of inferred profiles. I claim that progress on personalized services depends not on development of new algorithms, but rather on the integration of existing methods in novel ways. This talk describes joint work with Nicolas Fiechter, Melinda Gervasio, Wayne Iba, Mehmet Goker, Seth Rogers, and Cynthia Thompson.
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Date
2025-02-06
Extent
59:36 minutes
Resource Type
Moving Image
Resource Subtype
Lecture
Rights Statement
Unless otherwise noted, all materials are protected under U.S. Copyright Law and all rights are reserved