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» Troubleshooting Distributed Systems via Data Mining
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SIGIR
2003
ACM
14 years 23 days ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 8 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
ICDAR
2003
IEEE
14 years 24 days ago
A Scalable Solution for Integrating Illustrated Parts Drawings into a Class IV Interactive Electronic Technical Manual
This paper discusses a scalable solution for integrating legacy illustrated parts drawings into a Class IV Interactive Electronic Technical Manual (IETM) [1,2]. An IETM is an inte...
Molly L. Boose, David B. Shema, Lawrence S. Baum
WECWIS
2000
IEEE
144views ECommerce» more  WECWIS 2000»
13 years 12 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...
AISADM
2005
Springer
14 years 1 months ago
Execution Engine of Meta-learning System for KDD in Multi-agent Environment
Meta-learning system for KDD is an open and evolving platform for efficient testing and intelligent recommendation of data mining process. Metalearning is adopted to automate the s...
Ping Luo, Qing He, Rui Huang, Fen Lin, Zhongzhi Sh...