Sciweavers

917 search results - page 100 / 184
» Mining interesting sets and rules in relational databases
Sort
View
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
15 years 10 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
ICTAI
2006
IEEE
15 years 3 months ago
Sustained Emerging Spatio-Temporal Co-occurrence Pattern Mining: A Summary of Results
Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs i...
Mete Celik, Shashi Shekhar, James P. Rogers, James...
AUSAI
2003
Springer
15 years 3 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
KDD
2002
ACM
106views Data Mining» more  KDD 2002»
15 years 10 months ago
Selecting the right interestingness measure for association patterns
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava
CORR
2010
Springer
166views Education» more  CORR 2010»
14 years 10 months ago
A CHAID Based Performance Prediction Model in Educational Data Mining
The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors,...
M. Ramaswami, R. Bhaskaran