319 search results - page 5 / 64 » Algorithms for Mining Distance-Based Outliers in Large Datas... |
AI
2005
Springer
15 years 3 months ago
2005
Springer
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...
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KDD
2012
ACM
13 years 10 days ago
2012
ACM
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
SDM
2010
SIAM
14 years 11 months ago
2010
SIAM
Given large, multi-million node graphs (e.g., FaceBook, web-crawls, etc.), how do they evolve over time? How are they connected? What are the central nodes and the outliers of the...
EDBT
2000
ACM
15 years 1 months ago
2000
ACM
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
SIGMOD
2000
ACM
15 years 2 months ago
2000
ACM
For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or the outliers, can be more interesting than finding the common pattern...