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ICDCS
2002
IEEE
15 years 5 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
118
Voted
HPDC
2006
IEEE
15 years 6 months ago
Troubleshooting Distributed Systems via Data Mining
Through massive parallelism, distributed systems enable the multiplication of productivity. Unfortunately, increasing the scale of available machines to users will also multiply d...
David A. Cieslak, Douglas Thain, Nitesh V. Chawla
113
Voted
WECWIS
2000
IEEE
144views ECommerce» more  WECWIS 2000»
15 years 5 months ago
An Architecture to Support Distributed Data Mining Services in E-Commerce Environments
This paper presents our hybrid architectural model for Distributed Data Mining (DDM) which is tailored to meet the needs of e-businesses where application service providers sell D...
Shonali Krishnaswamy, Arkady B. Zaslavsky, Seng Wa...
95
Voted
ICDE
2007
IEEE
96views Database» more  ICDE 2007»
15 years 4 months ago
Mining Software Data
Data mining techniques and machine learning methods are commonly used in several disciplines. It is possible that they could also provide a basis for quality assessment of softwar...
Burak Turhan, F. Onur Kutlubay
114
Voted
OOPSLA
2004
Springer
15 years 6 months ago
A framework for detecting, assessing and visualizing performance antipatterns in component based systems
Component-based enterprise systems often suffer from performance issues as a result of poor system design. In this paper, we propose a framework to automatically detect, assess an...
Trevor Parsons