An Automated Privacy Information Detection Approach for Protecting Individual Online Social Network Users

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aut.relation.conference33rd Annual Conference of the Japanese Society for Artificial Intelligenceen_NZ
aut.researcherHutcheson, Catherine
dc.contributor.authorLi, Wen_NZ
dc.contributor.authorWu, Jen_NZ
dc.contributor.authorQuan, Ben_NZ
dc.date.accessioned2020-04-16T03:21:42Z
dc.date.available2020-04-16T03:21:42Z
dc.date.copyright2019en_NZ
dc.date.issued2019en_NZ
dc.description.abstractMassive private messages are posted by online social network users unconsciously every day, some users may face undesirable consequences. Thus, many studies have been dedicated to privacy leakage analysis. Whereas, there are very few studies detect privacy revealing for individual users. With this motivation, this paper aims to propose an automated privacy information detection approach to effectively detect and prevent privacy leakage for individual users. Based on the experimental results and case studies, the proposed model carries out a considerable performance.
dc.identifier.citationProceedings of the Annual Conference of JSAI, 2019, Volume JSAI2019, 33rd Annual Conference, 2019, Session ID 3H3-E-3-05, Pages 3H3E305, Released June 01, 2019
dc.identifier.doi10.11517/pjsai.JSAI2019.0_3H3E305en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/13272
dc.publisherThe Japanese Society for Artificial Intelligence
dc.relation.urihttps://www.jstage.jst.go.jp/article/pjsai/JSAI2019/0/JSAI2019_3H3E305/_article/-char/enen_NZ
dc.rightsJ-STAGE promotes "open access", which consists of (1) free access to articles and (2) specifying the scope of reuse like modification or redistribution. Over 90% of articles on J-STAGE are free to read. Articles displaying a CC license can be reused under the terms of the license.
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectAgent-based privacy protection; NLP; Deep learning
dc.titleAn Automated Privacy Information Detection Approach for Protecting Individual Online Social Network Usersen_NZ
dc.typeConference Contribution
pubs.elements-id373737
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS
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