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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Roffo, G. Segalin, C. Vinciarelli, A. Murino, V. Cristani, M. |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Comput. Sci., Univ. of Glasgow, Glasgow, UK (Vinciarelli, A.) || Dept. of Comput. Sci., Univ. of Verona (IT), Verona, Italy (Roffo, G.; Segalin, C.; Murino, V.; Cristani, M.) |
| Abstract | Identity safekeeping has recently become an important problem for the social web: as a case study, we focus here on instant messaging platforms, proposing novel soft-biometric cues for user recognition and verification. Specifically, we design a set of features encoding effectively how a person converses: since chats are crossbreeds of written text and face-to-face verbal communication, the features inherit equally from textual authorship attribution and conversational analysis of speech. Importantly, our cues ignore completely the semantics of the chat, relying solely on non-verbal aspects, taking care of possible privacy and ethical issues. We apply our approach on a novel dataset of 94 different individuals, whose chat conversations have been recorded for an average period of five months; recognition rate, intended as normalized AUC on CMC curve, is 95.73%, while verification rate amounts to 95.66%, as normalized AUC on ROC curve. |
| Starting Page | 99 |
| Ending Page | 104 |
| File Size | 992278 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479907038 |
| DOI | 10.1109/AVSS.2013.6636623 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-08-27 |
| Publisher Place | Poland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Histograms Correlation Feature extraction Educational institutions Data mining Probes Standards |
| Content Type | Text |
| Resource Type | Article |
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