Session details: KM graph mining
Abstract
- Session details: KM graph mining
Recommendations
Mining frequent cross-graph quasi-cliques
Joint mining of multiple datasets can often discover interesting, novel, and reliable patterns which cannot be obtained solely from any single source. For example, in bioinformatics, jointly mining multiple gene expression datasets obtained by different ...
Mining Frequent Subgraph Patterns from Uncertain Graph Data
In many real applications, graph data is subject to uncertainties due to incompleteness and imprecision of data. Mining such uncertain graph data is semantically different from and computationally more challenging than mining conventional exact graph ...
On mining cross-graph quasi-cliques
KDD '05: Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data miningJoint mining of multiple data sets can often discover interesting, novel, and reliable patterns which cannot be obtained solely from any single source. For example, in cross-market customer segmentation, a group of customers who behave similarly in ...
Comments
Information & Contributors
Information
Published In
- General Chairs:
- David Cheung,
- Il-Yeol Song,
- Program Chairs:
- Wesley Chu,
- Xiaohua Hu,
- Jimmy Lin
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Qualifiers
- Section
Conference
Acceptance Rates
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in