LIFESTYLE FINDER: Intelligent User Profiling Using Large-Scale Demographic Data
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A number of approaches have been advanced for taking data about a user's likes and dislikes and generating a general profile of the user. These profiles can be used to retrieve documents matching user interests; recommend music, movies, or other similar products; or carry out other tasks in a specialized fashion. This article presents a fundamentally new method for generating user profiles that takes advantage of a large-scale database of demographic data. These data are used to generalize user-specified data along the patterns common across the population, including areas not represented in the user's original data. I describe the method in detail and present its implementation in the LIFESTYLE FINDER agent, an internet-based experiment testing our approach on more than 20,006 users worldwide.
[1] Bruce Krulwich,et al. Learning user information interests through extraction of semantically significant phrases , 1996 .
[2] Michael J. Weiss,et al. The Clustering of America , 1988 .
[3] Beerud Dilip Sheth,et al. A learning approach to personalized information filtering , 1994 .
[4] Michael J. Pazzani,et al. Syskill & Webert: Identifying Interesting Web Sites , 1996, AAAI/IAAI, Vol. 1.
[5] Pattie Maes,et al. Collaborative Interface Agents , 1994, AAAI.