06月05日(Wed) 15:00〜17:40 C会場(-国際会議場202号室)
| 演題番号 | 2C4-IOS-3c-7 |
|---|---|
| 題目 | The Hybrid of PSO and SOM for Blog Success Prediction |
| 著者 | Hsu Chi-I(Kainan University) Wu Shelly P.J.(National Sun Yat-Sen University) Chiu Chaochang(Yuan Ze University) |
| 時間 | 06月05日(Wed) 17:00〜17:20 |
| 概要 | Particle Swarm Optimization (PSO) is a population-based optimization method simulating the social behavior of populations. Self-Organizing Map (SOM) is a neural network technique with good clustering performance. This research proposes the hybrid PSO and SOM for predicting Blog success level. Basically, PSO algorithm is adopted to find the optimal weights of the input variables of SOM, to reinforce the data in a single cluster (or certain clusters) with the same outcome level. A research model of Blog Success was proposed and 210 valid samples were collected from Internet users with Blog using or building experience. Compared with other prediction methods, the PSO-SOM approach of yielded better results than those of C5.0, Classification and Regression Trees (CART), Support Vector Machine (SVM) for 10-fold cross-validation. |
| 論文 | PDFファイル |