Application of loan lost-linking customer path correlated index model and network sorting search algorithm based on big data environment

Collaborative Search Model for Lost-Link Borrowers Information Based on Multi-Agent Q-Learning

“…For instance, Pang et al proposed an information-matching model and multi-angle tracking algorithm for LBs based on a family mobile social-contact big data network and achieved information matching for LBs [28]. Based on the daily consumption transaction network of LBs, a network sorting search rule and algorithm is proposed to track LBs in different address types [29]. However, the above-mentioned studies regarding tracking the information of LBs relied on complete household mobile phone records and consumption records, which had to be historical data from within the last six months; otherwise, the prediction results would be inaccurate.…”

Special issue on 2021 international conference on machine learning and big data analytics for iot security and privacy

“…Through the research on the application of convolutional neural network in the field of image segmentation, the problems of low segmentation accuracy, long time and high cost in the task of aerial image building image segmentation are solved to a certain extent [8]. Pang et al [9] propose the network sorting rules and searching rules, and construct the network sorting search algorithm to track loan lost-linking customers in different address types. In the preprocessing of gesture images, an improved Otsu method is proposed to improve the real-time performance to realize the threshold segmentation of the human hand; then the morphological processing is carried out, and the median filter method is used to achieve image denoising to improve image quality [10].…”