Study on E-Commerce Trust Prediction Mode Based on Combination Parameters

Abstract:

Based on the prediction of individual parameter and the theory of the correlation coefficient, it proposes a combination parameter trust prediction model to solve the parameter weights. The model takes correlation coefficient as the weight of the single parameter, and trust evaluation and prediction analysis is conducted in the form of combined indictors. The method of taking the single item parameters as the foundation of forecasting can increase a variety of items in the forecast parameters dynamically. At the same time, using correlation coefficient as the form of weight can maximize the weights of some parameters with high accuracy and reduce the weight of some parameters with poor accuracy. At last, an optimization algorithm of combination parameters prediction model is designed, and experiments show that the proposed combination parameters trust prediction model of e-commerce has a better accuracy compared to several other typical prediction models.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 2944-2952
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.2944
• Online since: December 2012
• Authors: Shao Zhong Zhang, Hai Dong Zhong
• Keywords: Combination Parameter, E-Commerce Trust, Prediction Model

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