Conference Paper

Accuracy in Rating and Recommending Item Features.

Vrije Universiteit, Amsterdam, The Netherlands
DOI: 10.1007/978-3-540-70987-9_19 Conference: Adaptive Hypermedia and Adaptive Web-Based Systems, 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings
Source: DBLP


This paper discusses accuracy in processing ratings of and recommendations for item features. Such processing facilitates feature- based user navigation in recommender system interfaces. Item features, often in the form of tags, categories or meta-data, are becoming impor- tant hypertext components of recommender interfaces. Recommending features would help unfamiliar users navigate in such environments. This work explores techniques for improving feature recommendation accu- racy. Conversely, it also examines possibilities for processing user ratings of features to improve recommendation of both features and items. This work's illustrative implementation is a web portal for a museum collection that lets users browse, rate and receive recommendations for both artworks and interrelated topics about them. Accuracy measure- ments compare proposed techniques for processing feature ratings and recommending features. Resulting techniques recommend features with relative accuracy. Analysis indicates that processing ratings of either fea- tures or items does not improve accuracy of recommending the other.

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