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A New Approach in Bloggers Classification with Hybrid of K-Nearest Neighbor and Artificial Neural Network Algorithms

Affiliations

  • Department of Computer Engineering, Hacettepe University, Beytepe, Ankara, Turkey
  • Young Researchers and Elite Club, Dehdasht Branch, Islamic Azad University, Dehdasht, Iran, Islamic Republic of
  • Young Researchers and Elite Club, Urmia Branch, Islamic Azad University, Urmia, Iran, Islamic Republic of

Abstract


Blogs are one of the effective tools of web2 which are considered as one of the major module and of social and interactive capabilities in making IT world wonderful for the cyber and virtual living. Two methods were used in this paper: K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANNs). These methods are classified based on Kohkiloye and Boyer Ahmad province bloggers dataset considering input features of each blogger to the other methods and previously provided algorithms as more optimal. Our simulation and experiments not only provide hopeful results but also higher anticipation and classification rate.

Keywords

Artificial Neural Networks, Bloggers Classification, Decision Tree, K-Nearest Neighbor.

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References


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