¹Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan, R.O.C.
²Department of Electrical Engineering, Feng Chia University, Taichung 40724, Taiwan, R.O.C.
³Department of Electrical Engineering, Feng Chia University, Taichung 40724, Taiwan, R.O.C.

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Abstract—Finding similar users in a community network is a very important part of the recommendation system. Traditionally, algorithms of this kind are based on a single condition to search for similar users. In recent years, some scholars have proposed the popular multi-criteria algorithm Skyline Query to search for similar users. However, their proposed methods might have found users not similar to the target user and are subject to the problem of slow execution. To solve these issues, this paper introduces the concepts of neural-based skyline region and neural network. The simulation results have verified the effectiveness and execution efficiency of the target method.

Index Terms—Social network, skyline query, neural network.

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Cite: Chun-Ching Hou, Che-Kai Chang, Yi-Chung Chen, Heng-Yi Su, Yu-Liang Hsu, "Finding Similar Users in Social Networks by Using the Neural-Based Skyline Region," Journal of Computers vol. 10, no. 5, pp. 292-299, 2015.