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Erschienen in: Computing 7/2015

01.07.2015

A survey on context-aware recommender systems based on computational intelligence techniques

verfasst von: Assad Abbas, Limin Zhang, Samee U. Khan

Erschienen in: Computing | Ausgabe 7/2015

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Abstract

The demand for ubiquitous information processing over the Web has called for the development of context-aware recommender systems capable of dealing with the problems of information overload and information filtering. Contemporary recommender systems harness context-awareness with the personalization to offer the most accurate recommendations about different products, services, and resources. However, such systems come across the issues, such as sparsity, cold start, and scalability that lead to imprecise recommendations. Computational Intelligence (CI) techniques not only improve recommendation accuracy but also substantially mitigate the aforementioned issues. Large numbers of context-aware recommender systems are based on the CI techniques, such as: (a) fuzzy sets, (b) artificial neural networks, (c) evolutionary computing, (d) swarm intelligence, and (e) artificial immune systems. This survey aims to encompass the state-of-the-art context-aware recommender systems based on the CI techniques. Taxonomy of the CI techniques is presented and challenges particular to the context-aware recommender systems are also discussed. Moreover, the ability of each of the CI techniques to deal with the aforesaid challenges is also highlighted. Furthermore, the strengths and weaknesses of each of the CI techniques used in context-aware recommender systems are discussed and a comparison of the techniques is also presented.

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Metadaten
Titel
A survey on context-aware recommender systems based on computational intelligence techniques
verfasst von
Assad Abbas
Limin Zhang
Samee U. Khan
Publikationsdatum
01.07.2015
Verlag
Springer Vienna
Erschienen in
Computing / Ausgabe 7/2015
Print ISSN: 0010-485X
Elektronische ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-015-0448-7

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