【摘 要】
：
Mining potential users in micro-blogging network,establishing the appropriate follow predictors and models for active micro-bloggers are very important for increasing the number of fans,and enhancing
【机 构】
：
School of Management and Economics,University of Electronic Science and Technology of China,Chengdu
【出 处】
：
2014年国际计算机科学与软件工程学术会议
论文部分内容阅读
Mining potential users in micro-blogging network,establishing the appropriate follow predictors and models for active micro-bloggers are very important for increasing the number of fans,and enhancing dissemination of information.Micro-blogging fans model is employed to predict potential active fans.The main influence factors such as popularity,activity,interest similarity are viewed as the core follow predictor.Fuzzy proximal support vector machine is used as a forecasting tool which fuzzy membership algorithm is optimized for reducing the complexity of the predict model.Experimental results show that,compared with other support vector machine model and fuzzy algorithm,predictor and prediction methods proposed in this paper have higher prediction accuracy and stability of the predicted results.
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