| dc.contributor | 傳播學院 | zh_TW |
| dc.creator (作者) | 許志堅 | zh_TW |
| dc.date (日期) | 2016-11 | |
| dc.date.accessioned | 19-Jun-2018 15:27:23 (UTC+8) | - |
| dc.date.available | 19-Jun-2018 15:27:23 (UTC+8) | - |
| dc.date.issued (上傳時間) | 19-Jun-2018 15:27:23 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/117811 | - |
| dc.description.abstract (摘要) | In this paper, we proposed an efficient spamfiltering method based on decision tree data mining technique, analyzed the as-sociation rules about spams, and applied these rules to develop a systematized spamfiltering method. Our method possessedthe following three major superiorities: (i) checking only an e-mail’s header section to avoid the low-operating efficiency inscanning an e-mail’s content. Moreover, the accuracy offiltering was enhanced simultaneously. (ii) In order that the probablemisjudgment in identifying an unknown e-mail could be“reversed”, we had constructed a reversing mechanism to help theclassification of unknown e-mails. Thus, the overall accuracy of ourfiltering method will be increased. (iii) Our method wasequipped with a re-learning mechanism, which utilized the supervised machine learning method to collect and analyze eachmisjudged e-mail. Therefore, the revision information learned from the analysis of misjudged e-mails incrementally gavefeedback to our method, and its ability of identifying spams would be improved. | en_US |
| dc.format.extent | 933977 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Security and Communication Networks 【SCI-E】, Vol.9, No.17, pp.4013-4026 | zh_TW |
| dc.subject (關鍵詞) | spam; data mining; decision tree | en_US |
| dc.title (題名) | An intelligent three‐phase spam filtering method based on decision tree data mining | en_US |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1002/sec.1584 | |
