DETEKSI E-MAIL DAN SPAM MENGGUNAKAN FUZZY ASSOCIATION RULE MINING
نویسندگان
چکیده
منابع مشابه
Rule-Based Spam E-mail Annotation
A new system for spam e-mail annotation by end-users is presented. It is based on the recursive application of hand-written annotation rules by means of an inferential engine based on Logic Programming. Annotation rules allow the user to express nuanced considerations that depend on deobfuscation, word (non)occurrence and structure of the message in a straightforward, human-readable syntax. We ...
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In the Association Rule Mining (ARM) approach, equal weight is assigned to all itemsets in the dataset. Hence, it is not appropriate for all datasets. The weight should be assigned based on the significance of each itemset. The WARM reduces extra steps during the generation of rules. As, the Weighted ARM (WARM) uses the significance of each itemset, it is applied in the data mining. The Fuzzy-b...
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Now-a-days, mailbox management has become a big task. A large proportion of the emails we receive are spam. These unwanted emails clog the inbox and are very ubiquitous. Here, a new technique for spam detection is presented that makes use of clustering and association rules generated by the Apriori algorithm. Vector space notation is used to represent the emails. The results obtained from exper...
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ژورنال
عنوان ژورنال: JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
سال: 2017
ISSN: 2540-8984
DOI: 10.29100/jipi.v2i2.348