{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T15:13:23Z","timestamp":1696086803139},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684369","type":"print"},{"value":"9781643684376","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,28]]},"abstract":"<jats:p>Heterogeneous Information Networks (HINs) are prevalent in real-world systems. Recent advances in network embedding provide an effective way of encoding HINs into low-dimensional vectors. However, there is a growing concern that existing HIN embedding algorithms may suffer from the problem of generating biased representations, resulting in discrimination against certain demographic groups. In this paper, we propose a flexible debiasing framework for fair HIN embedding to address this issue. Specifically, we first formalize measurements and the definition of fairness in HIN embedding. Then, we propose a debiasing framework named FairHGNN, including a novel meta-path sampling method that focuses on mitigating the bias in random walks, and a fairness constraint with Wasserstein distance to alleviate the algorithmic bias in Graph Neural Networks (GNNs). Experimental results on real-world datasets validate the efficacy of FairHGNN in promoting fairness and maintaining good utility.<\/jats:p>","DOI":"10.3233\/faia230289","type":"book-chapter","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:01:49Z","timestamp":1695978109000},"source":"Crossref","is-referenced-by-count":0,"title":["A Flexible Debiasing Framework for Fair Heterogeneous Information Network Embedding"],"prefix":"10.3233","author":[{"given":"Meng","family":"Cao","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Nanjing University, Nanjing, China, caomeng@smail.nju.edu.cn, chenmc@smail.nju.edu.cn, sjq@smail.nju.edu.cn, cxfang@smail.nju.edu.cn, chjwang@nju.edu.cn."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingcai","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Nanjing University, Nanjing, China, caomeng@smail.nju.edu.cn, chenmc@smail.nju.edu.cn, sjq@smail.nju.edu.cn, cxfang@smail.nju.edu.cn, chjwang@nju.edu.cn."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqing","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Nanjing University, Nanjing, China, caomeng@smail.nju.edu.cn, chenmc@smail.nju.edu.cn, sjq@smail.nju.edu.cn, cxfang@smail.nju.edu.cn, chjwang@nju.edu.cn."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenxuan","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Nanjing University, Nanjing, China, caomeng@smail.nju.edu.cn, chenmc@smail.nju.edu.cn, sjq@smail.nju.edu.cn, cxfang@smail.nju.edu.cn, chjwang@nju.edu.cn."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chongjun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Nanjing University, Nanjing, China, caomeng@smail.nju.edu.cn, chenmc@smail.nju.edu.cn, sjq@smail.nju.edu.cn, cxfang@smail.nju.edu.cn, chjwang@nju.edu.cn."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2023"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230289","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:01:50Z","timestamp":1695978110000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230289"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,28]]},"ISBN":["9781643684369","9781643684376"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230289","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,28]]}}}