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

Framework for Computing Trust in Online Short-Rent Platform Using Feature Selection of Images and Texts

【目的】提出新的在线短租平台信任计算框架,提供多组低维信任特征供用户选择展示个人信息,缓解隐私保护造成数据缺失导致无法评估信任的问题。【方法】融合图像和文本数据分析,使用进化算法结合粗糙集特征选择算法获得多组信任特征。【结果】新信任计算框架在保持信任预测精度不变情况下,信任特征降维后,维度约为原特征集的5%。【局限】仅对国内代表性平台进行数据分析,可扩展到国外平台数据。【结论】图像和文本分析为在线短租平台信任计算引入新视觉,所提出的信任计算框架可提供多组低维信任特征,可有效缓解信任计算中数据缺失和隐私受侵犯等问题。

[Objective] This paper proposes a novel framework to compute consumer trust of online short-rent platform. It provides multiple groups of low-dimension feature subsets for users to present their personal information, which addresses the issues of missing data. [Methods] We used rough-set feature selection based on evolutionary algorithm to extract information from images and texts. [Results] The proposed framework reduced dimension to 5% of the original feature set while classification accuracy remained unchanged. [Limitations] More research is needed to examine our model with data from overseas platforms. [Conclusions] The proposed framework could effectively compute users’ trust while protecting their privacy.