Abstract
Evaluation and recommendation are different actions, but they are consistent in mining and using information efficiently and effectively to improve their persuasiveness and accuracy. From the view of information processing, the paper builds a two-dimensional graph model which expresses the relationships between evaluators and objects. This graph model reflects the original information of evaluation or recommendation systems and has its equivalent matrix form. Next, the principle of matrix projection can be applied to get the evaluation or recommendation vector by solving the matrix maximization problems. What’s more, a rating data set of online move is selected to verify the model and method. In conclusion, from the example analysis, it is found that the proposed evaluation method is reasonable, and from the numerical experimental comparison, the proposed recommendation method is proved to be time-saving and more accurate than the generally adopted recommendation methods.
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Li, Y., Sun, J., Wang, K., Zheng, A. (2011). Evaluation and Recommendation Methods Based on Graph Model. In: Hu, B., Liu, J., Chen, L., Zhong, N. (eds) Brain Informatics. BI 2011. Lecture Notes in Computer Science(), vol 6889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23605-1_26
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DOI: https://doi.org/10.1007/978-3-642-23605-1_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23604-4
Online ISBN: 978-3-642-23605-1
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