A Survey on Approaches to Adaptation on the Web

A Survey on Approaches to Adaptation on the Web

Jorge Marx Gómez (Oldenburg University, Germany) and Thanh Tran (Karlsruhe University, Germany)
Copyright: © 2009 |Pages: 17
DOI: 10.4018/978-1-60566-222-0.ch007
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Abstract

Approaches to adaptation have been proposed by many different research communities, Hypermedia System and Intelligent Tutoring in particular. The task of adaptation breaks down to a mediation of resource provision and resource demand. In doing so, it is necessary to obtain some representation of them, either directly or through intermediate models that can be further processed to arrive at this information. Correspondingly, major differences in adaptation approaches manifest themselves in the employed sources, the way they are represented and the techniques used to derive the user demand from them. Therefore, we like to structure this survey according to these model-related aspects.
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Overview Of Adaptation Approaches

Single-Model Adaptation

Adaptive functionalities of many general information systems, commercial recommendation systems in web stores (EBay, 2005) (Amazon, 2005), are implemented through filtering-based approaches (Schafer, Konstan, Riedi, 1999). As discussed below, they exploit information extracted from usage as well as from the content of the resources in order to suggest further items potentially interesting to the user. In this regard, filtering denotes the mining of (meta-) relationships between users and contents useful for recommendations.

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