{"title":"WhatFits- Deep Learning for Clothing Collocation","authors":"Shengqiong Yuan, Luo Zhong, Lin Li","doi":"10.1109/BESC51023.2020.9348320","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348320","url":null,"abstract":"With the great development of 5G technology research and the constant development of the network shopping, clothing classification and clothing collocation recommendation based on clothing pictures can provide advices to the customer and help businesses to promote sales. Deep learning is a latest research achievement in the field of machine learning, it has a strong ability of image modeling and image representation, which makes breakthrough progress in the field of image processing. Based on image data of dressing commodities provided by Taobao.com, as well as the text data of both customers' historical behaviors and dressing outfits generated by fashion experts, we design and implement clothing collocation and recommendation through relevant technologies of data mining and deep learning.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Influence of National Identity on Prosocial Behavior: The Mediating and Moderating Role of Subjective Perceptions of COVID-19 Pandemic","authors":"Li Zhao, Di Chen, Xintao Li, Jian Guan","doi":"10.1109/BESC51023.2020.9348316","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348316","url":null,"abstract":"The prosocial behavior plays an important role in the containing of COVID-19 pandemic. The factors that could impact prosocial behavior and its facilitation mechanisms need further investigation. In this study, the effects of individuals' national identity and subjective perceptions of the COVID-19 pandemic on prosocial behavior were explored. From February to March 2020, 256 questionnaires were obtained. The national identity, prosocial behavior, and perceptions of the degrees of severity, scarcity of resources, controllability, and familiarity of the pandemic were measured. It is found that the prosocial behavior increases with national identity. The perception of the degree of severity of the pandemic plays a moderating role in the relationship between the national identity and prosocial behavior. To the ingroup prosocial behavior, there is no significant interaction between the national identity and the degree of perceived severity. Nevertheless, the outgroup prosocial behavior was more impacted by national identity when the perception of the degree of severity was relatively low. Additionally, the perception of the degree of controllability plays a mediating role in the relationship between the national identity and prosocial behavior (especially to the outgroup). In conclusion, the national identity and subjective perceptions of the COVID-19 epidemic affect the prosocial behavior, but with different impact mechanisms on ingroup and outgroup members. To accomplish the great success in combating the COVID-19 pandemic by promoting prosocial behavior, the society, government, and individuals should facilitate the national identity and advance the understanding of the epidemic.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132023624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How Many Orders does a Spoofer Need? - Investigation by Agent-Based Model -","authors":"T. Mizuta","doi":"10.1109/BESC51023.2020.9348308","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348308","url":null,"abstract":"Most financial markets prohibit unfair trades as they reduce efficiency and diminish the integrity of the market. Spoofers place orders they have no intention of trading in order to manipulate market prices and profit illegally. Most financial markets prohibit such spoofing orders; however, further clarification is still needed regarding how many orders a spoofer needs to place in order to manipulate market prices and profit. In this study I built an artificial market model (an agent-based model for financial markets) to show how unbalanced buy and sell orders affect the expected returns, and I implemented the spoofer agent in the model. I then investigated how many orders the spoofer needs to place in order to manipulate market prices and profit illegally. The results indicate that showing more spoofing orders than waiting orders in the order book enables the spoofer to earn illegally, amplifies price fluctuation, and reduces the efficiency of the market.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127777654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}