Evaluation and recommendation methods based on graph model

Authors:
Yongli Li;Jizhou Sun;Kunsheng Wang;Aihua Zheng
Affiliations:
Beijing Institute of Information and Control, Beijing, China;Beijing Institute of Information and Control, Beijing, China;Beijing Institute of Information and Control, Beijing, China;Beijing Institute of Information and Control, Beijing, China
Venue:
BI'11 Proceedings of the 2011 international conference on Brain informatics
Year:
2011

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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 timesaving and more accurate than the generally adopted recommendation methods.