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Cited 2 time in webofscience Cited 3 time in scopus
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Spam mail filtering system using semantic enrichment

Authors
Kim, HJKim, HNJung, Jason J.Jo, GS
Issue Date
2004
Publisher
SPRINGER-VERLAG BERLIN
Citation
WEB INFORMATION SYSTEMS - WISE 2004, PROCEEDINGS, v.3306, pp 619 - 628
Pages
10
Journal Title
WEB INFORMATION SYSTEMS - WISE 2004, PROCEEDINGS
Volume
3306
Start Page
619
End Page
628
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/37635
DOI
10.1007/978-3-540-30480-7_64
ISSN
0302-9743
1611-3349
Abstract
As the Internet infrastructure has been developed, E-mail is regrarded as one of the most important methods for exchanging information because of easy usage and low cost. Meanwhile, exponentially growing unwanted mails in users' mailbox have been raised as a main problem. To solve this problem. researchers have suggested many methodologies that are based on Bayesian classification. The kind of system usually shows high performances of precision and recall. But they have several problems. First, it has a cold start problem, that is, training phase has to be done before execution of the system. The system must be trained about spam and non-spam mail. Second. its cost for filtering spam mail is higher than rule-based system. Third. if E-mail has only few terms those represent its contents, the filtering performance is fallen. In this paper, we have focused on the last issued problem and we suggest spam mail filtering system using Semantic Enrichment. For the experiment, we tested the performance by using the measurements like precision, recall, and F1-measure. As compared with Bayesian classifier, the proposed system obtained 4-1%. 10.5% and 7.64% of improved precision, recall and F1-measure, respectively.
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Jung, Jason J.
소프트웨어대학 (소프트웨어학부)
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