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Cluster Analysis methods are very important, popular data summarization techniques applied in diverse environments. These techniques retrieve the hidden patterns in large datasets in the form of characterized patterns which can be interpreted further in different contexts. Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis...
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...
With the development of the mobile Internet and streaming media technology, digital music has been accepted by many people. However, in the face of the massive music data on the Internet, users want to find favorite music is like looking for a needle in a haystack via traditional music indexing techniques. In this paper, an improved algorithm for personalized music recommendation based on tag information...
The rapid expansion of user data and geographic location data in the location-based social networking applications, it is become increasingly difficult for users to quickly and accurately find the information they need. The characteristics of the traditional friend recommendation algorithm are analyzed and discussed in this paper. In order to improve the performance of friend recommendation, we proposed...
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