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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Homem, N. Carvalho, J.P. |
| Copyright Year | 2011 |
| Description | Author affiliation: TULisbon - Instituto Superior Técnico, INESC-ID, R. Alves Redol 9, 1000-029 Lisboa, Portugal (Carvalho, J.P.) || TULisbon - Instituto Superior Técnico, INESC-ID, R. Alves Redol 9, 1000-029 Lisboa (Homem, N.) |
| Abstract | Fingerprint identification is a well-known technique in forensic sciences. The basic idea of identifying a subject based on a set of features left by the subject actions or behavior can be applied to other domains. Identifying a web user based on a user fingerprint is one such application. This paper considers the problem of extracting fingerprints from web usage logs and matching them with those obtained from a set of known users. It presents an innovative fuzzy fingerprint algorithm based on vector valued fuzzy sets. Used sites are used as base features to create the fingerprint. The assumption is that sites accessed by each user remain approximately stable and are distinctive. The paper presents the proposed algorithm and shows some experimental results that validate the approach. The use of fast and compact algorithms is critical due to the possible huge number of users, and allows this method to be used on near real time. |
| Starting Page | 2622 |
| Ending Page | 2629 |
| File Size | 580296 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424473151 |
| ISSN | 10987584 |
| e-ISBN | 9781424473175 |
| e-ISBN | 9781424473168 |
| DOI | 10.1109/FUZZY.2011.6007446 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-27 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fingerprint recognition Approximation algorithms Monitoring Feature extraction Algorithm design and analysis Radiation detectors Training data streams fuzzy fingerprints vector valued fuzzy sets similarity frequent elements approximate algorithms |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Theoretical Computer Science Software |
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