Building Electronic Commerce Recommendation System Based on Ontology Learning and BP Neural Network

Hong Sheng Xu; Qing Tan

doi:10.4028/www.scientific.net/AMR.718-720.1961

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 718-720Building Electronic Commerce Recommendation System...

Building Electronic Commerce Recommendation System Based on Ontology Learning and BP Neural Network

Abstract:

Electronic commerce recommendation system can effectively retain user, prevent users from erosion, and improve e-commerce system sales. BP neural network using iterative operation, solving the weights of the neural network and close values to corresponding network process of learning and memory, to join the hidden layer nodes of the optimization problem of adjustable parameters increase. Ontology learning is the use of machine learning and statistical techniques, with automatic or semi-automatic way, from the existing data resources and obtaining desired body. The paper presents building electronic commerce recommendation system based on ontology learning and BP neural network. Experimental results show that the proposed algorithm has high efficiency.

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Periodical:

Advanced Materials Research (Volumes 718-720)

Pages:

1961-1966

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.718-720.1961

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Online since:

July 2013

Authors:

Hong Sheng Xu, Qing Tan

Keywords:

BP Neural Network (BPNN), Electronic Commerce Recommendation System, Ontology Learning

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References

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