IEEE International Conference on Social Computing最新文献_第2页

Fairness-Aware Loan Recommendation for Microfinance Services 小额信贷服务的公平意识贷款建议

IEEE International Conference on Social Computing Pub Date : 2014-08-04 DOI: 10.1145/2639968.2640064

Eric L. Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chih Chen, Shou-de Lin, Yen-Sheng Chiang, Kuan-Ta Chen

{"title":"Fairness-Aware Loan Recommendation for Microfinance Services","authors":"Eric L. Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chih Chen, Shou-de Lin, Yen-Sheng Chiang, Kuan-Ta Chen","doi":"10.1145/2639968.2640064","DOIUrl":"https://doi.org/10.1145/2639968.2640064","url":null,"abstract":"Up to date, more than 15 billion US dollars have been invested in microfinance that benefited more than 160 million people in developing countries. The Kiva organization is one of the successful examples that use a decentralized matching process to match lenders and borrowers. Interested lenders from around the world can look for cases among thousands of applicants they found promising to lend the money to. But how can loan borrowers and lenders be successfully matched up in a microfinance platform like Kiva? We argue that a sophisticate recommender not only pairs up loan lenders and borrowers in accordance to their preferences, but should also help to diversify the distribution of donations to reduce the inequality of loans is highly demanded, as altruism, like any resource, can be congestible.\u0000 In this paper, we propose a fairness-aware recommendation system based on one-class collaborative-filtering techniques for charity and micro-loan platform such as Kiva.org. Our experiments on real dataset indicates that the proposed method can largely improve the loan distribution fairness while retaining the accuracy of recommendations.","PeriodicalId":206201,"journal":{"name":"IEEE International Conference on Social Computing","volume":"36 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126197913","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}

引用次数: 41

An Enhanced Collaborative Filtering with Flexible Item Popularity Control for Recommender Systems 基于灵活项目流行度控制的推荐系统增强协同过滤

IEEE International Conference on Social Computing Pub Date : 2014-08-04 DOI: 10.1145/2639968.2640058

Tu Chen, Hui Tian, Xuzhen Zhu

{"title":"An Enhanced Collaborative Filtering with Flexible Item Popularity Control for Recommender Systems","authors":"Tu Chen, Hui Tian, Xuzhen Zhu","doi":"10.1145/2639968.2640058","DOIUrl":"https://doi.org/10.1145/2639968.2640058","url":null,"abstract":"With the emerging and rapid development of Internet applications like social networks, E-commerce and so on, massive information has been created and stored. Recommender systems have been developed to deal with the information overload problem. Various recommendation algorithms have been proposed and Collaborative Filtering (CF) is one of the most remarkable. However, many similarity-based CFs suffer from a popularity bias problem: Popular items are frequently recommended not necessarily promoting the accuracy but making the recommendation lacking diversity. In this paper, we firstly explain how the item popularity impacts on the recommendation. Secondly, we propose an enhanced collaborative filtering approach (ECF) by adding item popularity control into a user-taste based method. Different from some other existing item popularity based CF methods, the popularity control in our approach is flexible and tunable. After that, extensive experiments are performed on two real benchmark datasets where the relationship between item popularity control and recommendation accuracy and diversity is investigated and turns out to be nonlinear. Experimental results demonstrate that temperate item popularity control can further improve the recommendation accuracy and diversity significantly, compared with the pure user-taste based method. But intemperate control makes the performance even worse Thus the flexibility is indeed essential and valuable.","PeriodicalId":206201,"journal":{"name":"IEEE International Conference on Social Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133121303","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}

引用次数: 2

A gender lens perspective of the use of social network in higher education in Malaysia and Australia 从性别视角看马来西亚和澳大利亚高等教育中社交网络的使用

IEEE International Conference on Social Computing Pub Date : 2014-08-04 DOI: 10.1145/2639968.2640070

Kung-Keat Teoh, Tahereh Pourshafie, V. Balakrishnan

{"title":"A gender lens perspective of the use of social network in higher education in Malaysia and Australia","authors":"Kung-Keat Teoh, Tahereh Pourshafie, V. Balakrishnan","doi":"10.1145/2639968.2640070","DOIUrl":"https://doi.org/10.1145/2639968.2640070","url":null,"abstract":"The use of social network sites (SNS) such as Facebook, Twitter, Linkedin, Pinterest, Google Plus+, Tumblr, and Instagram, among others, has increased at a very fast pace in the last few years. In tandem with its rising popularity, especially among teenagers, many academics in higher education have been experimenting with its use in formal and less formal ways, in classroom teaching. Studies on the use of SNS in higher education indicate mixed results. While some academics found that SNS only distracts students from actual study and do not improve academic performance, others discovered that it improves communication and teacher-student relationships. Most however, agree that SNS's popularity with students makes it a very useful tool to exploit for classroom teaching and management. There are very few studies which look into the effect of gender on the use of SNS in education. While studies have concluded that men and women approach and use SNS in slightly different ways, there is little in existing literature which tells us about how the use of SNS in higher education differs between men and women. This paper discusses research on the use of SNS in higher education by both genders. It details the results of a survey conducted in Malaysia and Australia and highlights how men and women perceive SNS use in higher education based on a framework built on Push Pull and Mooring theory.","PeriodicalId":206201,"journal":{"name":"IEEE International Conference on Social Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115670091","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}

引用次数: 5

Predicting Controversy of Wikipedia Articles Using the Article Feedback Tool 使用文章反馈工具预测维基百科文章的争议

IEEE International Conference on Social Computing Pub Date : 2014-08-04 DOI: 10.1145/2639968.2640074

Michal Jankowski-Lorek, R. Nielek, A. Wierzbicki, Kazimierz Zielinski

引用次数: 16

Enron Corporation: You're the Boss if People Get Mentioned to You 安然公司:如果别人向你提起，你就是老板

IEEE International Conference on Social Computing Pub Date : 2014-08-04 DOI: 10.1145/2639968.2640065

Apoorv Agarwal, Adinoyi Omuya, Jingwei Zhang, Owen Rambow

引用次数: 0

Models for Measuring Access Security of Web Application: Security Reference Model Web应用访问安全度量模型:安全参考模型

IEEE International Conference on Social Computing Pub Date : 2013-09-08 DOI: 10.1109/SocialCom.2013.166

Ana Cervigni Guerra, M. Pessôa

引用次数: 0

An Enhanced Collaborative Filtering with Flexible Item Popularity Control for Recommender Systems 基于灵活项目流行度控制的推荐系统增强协同过滤

IEEE International Conference on Social Computing Pub Date : 1900-01-01 DOI: 10.1145/2639968.2640076

Tu Chen, Hui Tian, Xuzhen Zhu

{"title":"An Enhanced Collaborative Filtering with Flexible Item Popularity Control for Recommender Systems","authors":"Tu Chen, Hui Tian, Xuzhen Zhu","doi":"10.1145/2639968.2640076","DOIUrl":"https://doi.org/10.1145/2639968.2640076","url":null,"abstract":"With the emerging and rapid development of Internet applications like social networks, E-commerce and so on, massive information has been created and stored. Recommender systems have been developed to deal with the information overload problem. Various recommendation algorithms have been proposed and Collaborative Filtering (CF) is one of the most remarkable. However, many similarity-based CFs suffer from a popularity bias problem: Popular items are frequently recommended not necessarily promoting the accuracy but making the recommendation lacking diversity. In this paper, we firstly explain how the item popularity impacts on the recommendation. Secondly, we propose an enhanced collaborative filtering approach (ECF) by adding item popularity control into a user-taste based method. Different from some other existing item popularity based CF methods, the popularity control in our approach is flexible and tunable. After that, extensive experiments are performed on two real benchmark datasets where the relationship between item popularity control and recommendation accuracy and diversity is investigated and turns out to be nonlinear. Experimental results demonstrate that temperate item popularity control can further improve the recommendation accuracy and diversity significantly, compared with the pure user-taste based method. But intemperate control makes the performance even worse Thus the flexibility is indeed essential and valuable.","PeriodicalId":206201,"journal":{"name":"IEEE International Conference on Social Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121678550","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}

引用次数: 0

The Role of Peer Influence in Churn in Wireless Networks 无线网络中同伴影响在用户流失中的作用

IEEE International Conference on Social Computing Pub Date : 1900-01-01 DOI: 10.1145/2639968.2640075

Qiwei Han, Pedro A. Ferreira

引用次数: 2

How to Become a More Popular Thread on Tianya Club 如何成为天涯俱乐部的热门话题

IEEE International Conference on Social Computing Pub Date : 1900-01-01 DOI: 10.1145/2639968.2640085

Jindong Chen, Lina Cao, Xijin J. Tang

引用次数: 0

A Pilot Study about Military Users and Information Systems: Exploring Military User Attitudes about Technology 关于军事用户和信息系统的初步研究:探索军事用户对技术的态度

IEEE International Conference on Social Computing Pub Date : 1900-01-01 DOI: 10.1109/SocialCom.2013.136

IV HarryD.Tunnell

引用次数: 2