کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
552821 | 873278 | 2009 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discovery of unapparent association rules based on extracted probability
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Association rule mining is an important task in data mining. However, not all of the generated rules are interesting, and some unapparent rules may be ignored. We have introduced an “extracted probability” measure in this article. Using this measure, 3 models are presented to modify the confidence of rules. An efficient method based on the support-confidence framework is then developed to generate rules of interest. The adult dataset from the UCI machine learning repository and a database of occupational accidents are analyzed in this article. The analysis reveals that the proposed methods can effectively generate interesting rules from a variety of association rules.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 47, Issue 4, November 2009, Pages 354–363
Journal: Decision Support Systems - Volume 47, Issue 4, November 2009, Pages 354–363
نویسندگان
Chia-Wen Liao, Yeng-Horng Perng, Tsung-Lung Chiang,