کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
536666 | 870597 | 2008 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
LDBOD: A novel local distribution based outlier detector
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
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چکیده انگلیسی
As an important research direction in KDD field, outlier detection has been drawing much attention from different communities. In this paper, two novel algorithms LDBOD and LDBOD+ for outlier detection are proposed. Similar to LOF, they also aim to find local outliers. However, LDBOD/LDBOD+ detects local outliers from the viewpoint of local distribution, which is characterized through three proposed measurements, local-average-distance, local-density, and local-asymmetry-degree. Several experiments were conducted to demonstrate the advantages of LDBOD/LDBOD+ compared with LOF.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 29, Issue 7, 1 May 2008, Pages 967–976
Journal: Pattern Recognition Letters - Volume 29, Issue 7, 1 May 2008, Pages 967–976
نویسندگان
Yong Zhang, Su Yang, Yuanyuan Wang,