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The existing content-based recommendation methods have two major limitations. First, due to the defects of the items and the user model matching algorithms, the recommendation results are very narrow. Second, scant attention is paid to the scenario, making the recommendation system not context-aware. It is essential to improve user satisfaction through high-quality recommendation. In this paper, two...
Online advertising has become an important marketing instrument for many enterprises, and the impact of enterprises’ online advertising has been increasing rapidly. Significant long-term enterprise profits are dynamically determined by the continuous online advertisement investment strategies implemented. This paper formulates the investment cost function which reflects the characteristics and impacts...
As many engineering optimization problems are rather complicated, it is usually necessary to search the optimal solution in a complex and huge search space. When faced with these large-scale problems, conventional optimization algorithms need to traverse the entire search space and it is impossible for them to finish the search within polynomial time. Moreover, it can’t meet requirements in terms...
PM2.5 hadn’t received much attention until 2013 when people started to understand its dreadful impacts to human health. According to the meteorological monitoring data of PM2.5 from September 9, 2016 to September 9, 2017 in Fuling district, Chongqing, this paper analyzed the impact of temperature, humidity and the power of wind on PM2.5. Using the mathematical model of BP neural networks, a prediction...
Processing high-dimensional remote sensing images data with conventional convolutional neural networks raises certain issues such as prolonged model convergence time, vanishing gradient, convergence of the non-minimum values, etc. due to its high time-complexity and random initialization parameters nature. Aiming at those issues, this article proposes a convolutional neural network remote sensing...
Diabetic is becoming a very serious disease today for the most of people all over the world due to the unhealthy food habits. For predicting the diabetes, we introduce a new diabetic diagnosis system which combines a newly proposed temporal feature selection and temporal fuzzy ant miner tree (TFAMT) classifier for effective decision making in type-2 diabetes analysis. Moreover, a new temporal weighted...
Rough set theory (RST) can be viewed as one of the classical set theory for handling with imprecision knowledge. The theory has discovered applications in numerous areas, for example, engineering, industries, environment and others. Churn in telecommunication sector, customer switching from one service provider to another. Predicting telecom customer churn is challenging due to the huge and inconsistent...
As spectra-based fault localization techniques report suspicious statements by analyzing the coverage of test cases, the effectiveness of the results is highly dependent on the composition of test suites. This paper proposes an approach for selecting a subset of the passed test suite when a failure revealed by a failed test case. The goal is to obtain a more effective fault localization using a minimal...
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