Machine Learning for User Modeling
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This paper examines a number of challenges for machine learning that have hindered its application in user modeling, including the need for large data sets; theneed for labeled data; concept drift; and computational complexity.Abstract:
At first blush, user modeling appears to be a prime candidate for straightforward application of standard machine learning techniques. Observations of the user's behavior can provide training examples that a machine learning system can use to form a model designed to predict future actions. However, user modeling poses a number of challenges for machine learning that have hindered its application in user modeling, including: the need for large data sets; the need for labeled data; concept drift; and computational complexity. This paper examines each of these issues and reviews approaches to resolving them.read more
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Journal ArticleDOI
Adaptive Hypermedia
TL;DR: Adaptive hypermedia as mentioned in this paper is a relatively new direction of research on the crossroads of hypermedia and user modeling, which builds a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user.
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Generic User Modeling Systems
TL;DR: A review of the development of generic user modeling systems over the past twenty years is given in this article, which describes their purposes, their services within user-adaptive systems, and the different design requirements for research prototypes and commercially deployed servers.
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User Modeling for Adaptive News Access
TL;DR: The induction of hybrid user models that consist of separate models for short-term and long-term interests are proposed, and it is suggested that effective personalization can be achieved without requiring any extra effort from the user.
Journal ArticleDOI
Web Usage Mining as a Tool for Personalization: A Survey
TL;DR: This paper is a survey of recent work in the field of web usage mining for the benefit of research on the personalization of Web-based information services, focusing on the problems identified and the solutions that have been proposed.
Book ChapterDOI
Adaptive interfaces and agents
TL;DR: As its title suggests, this chapter covers a broad range of interactive systems, and one idea in common is that it can be worthwhile for a system to learn something about each individual user and adapt its behavior to them in some nontrivial way.
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