@inproceedings{oai:kumadai.repo.nii.ac.jp:00021647,
 author = {高下, 大輝 and Takashita, Taiki and 糸川, 剛 and Itokawa, Tsuyoshi and 北須賀, 輝明 and 有次, 正義 and 高下, 大輝 and Takashita, Taiki and 糸川, 剛 and Itokawa, Tsuyoshi and Kitasuka, Teruaki and Aritsugi, Masayoshi},
 book = {Knowledge-Based Intelligent Information and Engineering Systems},
 month = {Sep},
 note = {application/pdf, 論文(Article), In this paper a spam filtering method is proposed. We focus on user behavior that most email users browse the Web. The method reduces troublesome maintenance of the spam filter, since the filter learns from Web browsing behavior in the background. The method uses Web browsing behavior of each user to learn ham words. Ham words are picked up from browsed Web pages using TF-IDF and stored in the database called ham words list. For each received email, the method extracts keywords from the email, including Web pages of the URLs. If some keywords are in the ham words list, the email is treated as a ham. In our experiments, several spam emails which cannot be detected by a Bayesian filter are detected as spams., http://www.springerlink.com/content/1613j403161258p5/?p=7c77d411b23e44e6a3767b24506cdec0&pi=95},
 pages = {774--781},
 publisher = {Springer Verlag  (Germany)},
 title = {A Spam Filtering Method Learning from Web Browsing Behavior},
 volume = {5178},
 year = {2008},
 yomi = {タカシタ, タイキ and イトカワ, ツヨシ and タカシタ, タイキ and イトカワ, ツヨシ}
}