Paper Info
Title
Graph mining for discovering infrastructure patterns in configuration management databases.
Abstract
Abstract A configuration management database (CMDB) can be considered to be a large graph representing the IT infrastructure entities and their interrelationships. Mining such graphs is challenging because they are large, complex, and multi-attributed and have many repeated labels. These characteristics pose challenges for graph mining algorithms, due to the increased cost of subgraph isomorphism (for support counting) and graph isomorphism (for eliminating duplicate patterns). The notion of pattern frequency or support is also more challenging in a single graph, since it has to be defined in terms of the number of its (potentially, exponentially many) embeddings. We present CMDB-Miner, a novel two-step method for mining infrastructure patterns from CMDB graphs. It first samples the set of maximal frequent patterns and then clusters them to extract the representative infrastructure patterns. We demonstrate the effectiveness of CMDB-Miner on real-world CMDB graphs, as well as synthetic graphs.
Year
DOI
Venue
2012
10.1007/s10115-012-0528-3
Knowl. Inf. Syst.
Keywords
Field
DocType
Single graph mining,Frequent subgraphs,Sparse graph mining,Configuration management databases
Graph operations,Data mining,Configuration management database,Graph database,Graph isomorphism,Computer science,Theoretical computer science,Information technology management,Configuration management,Subgraph isomorphism problem,Graph (abstract data type)
Journal
Volume
Issue
ISSN
33
3
0219-3116
Citations 
PageRank 
References 
8
0.55
30
Authors
7
Name
Order
Citations
PageRank
Pranay Anchuri1502.27
Mohammed Javeed Zaki27972536.24
Omer Barkol31027.78
Ruth Bergman4457.05
Yifat Felder5242.09
Shahar Golan6575.72
Arik Sityon7191.54