Building the Data Warehouse,3rd Edition
Building the Data Warehouse,3rd Edition
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Dex: high-performance exploration on large graphs for information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Community evolution in dynamic multi-mode networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph OLAP: Towards Online Analytical Processing on Graphs
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Managing and Mining Graph Data
Managing and Mining Graph Data
On community outliers and their efficient detection in information networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying Evolving Groups in Dynamic Multimode Networks
IEEE Transactions on Knowledge and Data Engineering
Community mining from multi-relational networks
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
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There are a growing number of data-mining techniques that model and analyze data in the form of graphs. Graphs can link otherwise disparate data to form a holistic view of the dataset. Unfortunately, it can be challenging to manage the resulting large graph and use it during data analysis. To facilitate managing and operating on graphs, the Core-Facets model offers a framework for graph-based data warehousing. The Core-Facets model builds a heterogeneous attributed core graph from multiple data sources and creates facet graphs for desired analyses. Facet graphs can transform the heterogeneous core graph into various purpose-specific homogeneous graphs, thereby enabling the use of traditional graph analysis techniques. The Core-Facets model also supports new opportunities for multi-view data mining. This paper discusses an implementation of the Core-Facets model, which provides a data warehousing framework for tasks ranging from data collection to graph modeling to graph preparation for analysis.