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A locality sensitive k-means clustering approach has been presented recently. This approach can increase clustering accuracies. However, it is affected by the initial centers and often attain the unstable clustering results. In this paper, a novel locality sensitive k-means clustering algorithm based on subtractive clustering is proposed. The initial centers are produced by subtractive clustering...
Nowadays, the amount of the application in Android App Market has grown fast, and the android malwares have been introduced fast into that market, too. In this paper, we use static analysis of a given android application with intensive feature engineering which we focus on different sources and different levels. It means that we not only extract features from the executable file classes.dex but also...
With the prevalence of cloud storage, more and more users store their files in cloud storage. There are a large number of duplicate files in the cloud storage, which makes file deduplication important for saving the storage space. After analyzing the features of cloud files, this paper proposes a new file deduplication method based on differential bloom filter. Besides utilizing application aw are...
Subtractive clustering and k-harmonic means clustering are two of the popular clustering algorithms. However, k-harmonic means need generate some initial centers for its initialization, and subtractive clustering do not need the initialization. Therefore, subtractive clustering often cannot gain the better clustering performance. In this paper, a novel subtractive clustering is proposed. The new method...
This article describes a vehicle monitoring system client based on HTML and ASP.NET. It involves the HTML technology, ASP.NET technology, etc. with excellent compatibility and expansibility. Their key functions are sort cars according to their colors, query the vehicle list, vehicle state information display, data report, terminal controls, etc. According to the distribution and running state of vehicles...
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