期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：3
页码：179-188
DOI：10.14257/ijhit.2016.9.3.17
出版社：SERSC
摘要：A plethora of big data applications are emerging and being researched in the computer science community which require online classification and pattern recognition of huge data pools collected from sensor networks, image and video systems, online forum platforms, medical agencies etc. However, as an NP hard issue data mining techniques are facing with lots of difficulties. To deal with the hardship, we conduct research on the novel algorithm for data mining and knowledge discovery through network entropy. We firstly introduce necessary data analysis techniques such as support vector machine, neural network and decision tree methods. Later, we analyze the organizational structure of network graphical pattern with the knowledge of machine learning methodology and graph theory. Eventually, our modified method is finalized with decision and validation implementation. The simulation results of our approach on different databases show the feasibility and effectiveness of our proposed framework. As the final part, we provide our conclusion and prospect.
关键词：Pattern Analysis and Machine Intelligence; Data Classification Technique; ; Data Mining; Knowledge Discovery; Big Data and Information Security
