[Objective] A novel computational framework for trust in online short-rent platform is proposed. Multiple groups of low-dimension feature subsets are provided to users for presenting personal information, which contributes to ease the problem in trust computations caused by missing data. [Methods] Evolutionary algorithm based rough-set feature selection is used. Image and text analysis are used for feature extraction. [Results] The proposed framework reduces dimension into 5% of the original feature set with classification accuracy remaining unchanged. [Limitations] Further analysis could be done on overseas platform data. [Conclusions] The proposed framework could provide multiple groups of low-dimension feature subsets, which could help to ease the problem in trust computing caused by missing data and privacy.
梁家铭, 赵洁, 郑鹏, 黄流深, 叶敏祺, 董振宁. 特征选择下融合图像和文本分析的在线短租平台信任计算框架
[J]. 数据分析与知识发现, 0, (): 1-.
Jiaming Liang, Jie Zhao, Peng Zheng, Liushen Huang, Minqi Ye, Zhenning Dong. Image and text analysis based computational framework of trust in online short-rent platform using feature selection
. Data Analysis and Knowledge Discovery, 0, (): 1-.