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This paper uses GMDH method to establish a prediction model to forecast the output value of transport & storage of Guangdong in China, since the original samples of the output value of transport & storage are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective...
Fast and efficient delivery of targeted and personalized advertisements has become a staple in E-commerce. The field of market research targeting in online environments has seen extensive research on the topic of customer targeting, but most of the information detailing the process of profiling is closely guarded by the industry. Much of what is available tells that information such as cookies and...
This paper studies and proposes a method for learning the user's preferences and propsing recommendations on composite bundles of products and services. The user preferences are learned using a regression analysis on the historical purchase information. These learned preferences are used to infer a utility axis in the multi-dimensional utility space. Subsequently, the standard utility axes are adaptivelly...
Defect prediction is an important task in the mining of software repositories, but the quality of predictions varies strongly within and across software projects. In this paper we investigate the reasons why the prediction quality is so fluctuating due to the altering nature of the bug (or defect) fixing process. Therefore, we adopt the notion of a concept drift, which denotes that the defect prediction...
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