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Location-Aware and Personalized Collaborative Filtering for Web Service Recommendation : A Review

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Chinnu Priya J.V., Suja Rani M.S.
10.5120/ijca2016908089

Chinnu Priya J.V. and Suja Rani M.S.. Article: Location-Aware and Personalized Collaborative Filtering for Web Service Recommendation : A Review. International Journal of Computer Applications 133(14):1-3, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Chinnu Priya J.V. and Suja Rani M.S.},
	title = {Article: Location-Aware and Personalized Collaborative Filtering for Web Service Recommendation : A Review},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {14},
	pages = {1-3},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

As the number of web services with similar functionality increases, the service users usually depend on web recommendation systems.Now a days the service users pay more importance on non functional properties which are also known as Quality of Service(QoS) while finding and selecting appropriate web services. Collaborative filtering[3] approach predicts the QoS values of the web services effectively.Existing recommendation systems rarely consider the personalized influence of the users and services in determining the similarity between users and services.The proposed system is a ranking oriented hybrid approach which integrates user-based and item-based QoS predictions.Many of the non-functional properties depends on the user and the service location. The system thus employs the location information of users and services in selecting similar neighbors for the target user and service and thereby making personalized service recommendation for service users.

References

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Keywords

Web services, Collaborative filtering, Location-aware, QoS prediction, Service recommendation