کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
496439 862859 2012 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Rough sets for spam filtering: Selecting appropriate decision rules for boundary e-mail classification
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Rough sets for spam filtering: Selecting appropriate decision rules for boundary e-mail classification
چکیده انگلیسی

Nowadays, spam represents an extensive subset of the information delivered through Internet involving all unsolicited and disturbing communications received while using different services including e-mail, weblogs and forums. In this context, this paper reviews and brings together previous approaches and novel alternatives for applying rough set (RS) theory to the spam filtering domain by defining three different rule execution schemes: MFD (most frequent decision), LNO (largest number of objects) and LTS (largest total strength). With the goal of correctly assessing the suitability of the proposed algorithms, we specifically address and analyse significant questions for appropriate model validation like corpus selection, preprocessing and representational issues, as well as different specific benchmarking measures. From the experiments carried out using several execution schemes for selecting appropriate decision rules generated by rough sets, we conclude that the proposed algorithms can outperform other well-known anti-spam filtering techniques such as support vector machines (SVM), Adaboost and different types of Bayes classifiers.

Figure optionsDownload as PowerPoint slideHighlights
► Review of rough sets for spam filtering.
► Rule execution schemes for RS-generated rules.
► Theoretical and practical issues in anti-spam filtering domain.
► Content-based model evaluation for spam filtering.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 12, Issue 11, November 2012, Pages 3671–3682
نویسندگان
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