| Presentation | 2007-03-15 An online spam filtering system for changing situations using multiple classifiers Kenta NARUMI, Kyousuke NISHIDA, Koichiro YAMAUCHI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Spam mail is a serious problem now. To eliminate many spam mails, many spam mail filters referring mail bodies have been proposed. The filters with statistical learners (ex. Naive Bayes) are usually used because of its high accuracy. However, it is difficult for the filters to learn mails that have new tendency after learning of many mails. We have to solve this problem to deal with spam mails that are changing day by day. In contrast, there are filters with instance-based learners (ex. Nearest Neighbor) that are able to respond to the changes quickly. However, they are not used widely because they require large computational complexity and memory resources to store many mails. In this study, we proposed a spam filter that is able to respond to various changes by using an instance-based learner that store recent mails and using statistical learners built from enormous past mails. We showed the proposed spam filter achieved higher accuracy than other spam filters in experiments using real dataset. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | spam mail filter / multiple classifier systems / concept drift / online learning / baysian learning / instance-based learning |
| Paper # | PRMU2006-235 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2007/3/8(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An online spam filtering system for changing situations using multiple classifiers |
| Sub Title (in English) | |
| Keyword(1) | spam mail filter |
| Keyword(2) | multiple classifier systems |
| Keyword(3) | concept drift |
| Keyword(4) | online learning |
| Keyword(5) | baysian learning |
| Keyword(6) | instance-based learning |
| 1st Author's Name | Kenta NARUMI |
| 1st Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University() |
| 2nd Author's Name | Kyousuke NISHIDA |
| 2nd Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University |
| 3rd Author's Name | Koichiro YAMAUCHI |
| 3rd Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University |
| Date | 2007-03-15 |
| Paper # | PRMU2006-235 |
| Volume (vol) | vol.106 |
| Number (no) | 605 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |