Multi-Field-Oriented Personalized Recommendation

Jian Jun Li; Zheng De Zhao; Geng Geng Peng

doi:10.4028/www.scientific.net/AMM.513-517.416

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Multi-Field-Oriented Personalized Recommendation

Multi-Field-Oriented Personalized Recommendation

Abstract:

Considering the relationship among user-to-user, service-to-service, user-to-service, This paper use clustering algorithm to cluster the data, and then re-use model which is based on the population-based recommendation, the content-based recommendation, and collaborative filtering recommendation absorb their benefits and overcome their shortcomings, This paper proposed multi-personalized recommendation service model which is based on the full understanding between interrelated users and services. It can provide users with accurate and personalized service. We verified the model through experiments and carried out the proposed recommendation model drawn feasible.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

416-419

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.416

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Online since:

February 2014

Authors:

Jian Jun Li*, Zheng De Zhao, Geng Geng Peng

Keywords:

Clustering, Multi-Field, Personalized Service Recommendation

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