An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Substructure similarity search in graph databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Fg-index: towards verification-free query processing on graph databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Graph-Based Procedural Abstraction
Proceedings of the International Symposium on Code Generation and Optimization
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Taming verification hardness: an efficient algorithm for testing subgraph isomorphism
Proceedings of the VLDB Endowment
Graph aggregation based image modeling and indexing for video annotation
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
A relational-based approach for aggregated search in graph databases
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Graph-based approach for human action recognition using spatio-temporal features
Journal of Visual Communication and Image Representation
| Hi-index | 0.00 |
Graphs are widely used to model complicated data semantics in many applications (e.g. spacial databases, image databases,. . .). Querying graph databases is costly since it involves subgraph isomorphism testing, which is an NP-complete problem [7]. Most of the existing query processing techniques are based on the framework of filtering-and-verification to reduce computation costs. However, to the best f our knowledge, the problem of assembling graphs to provide an answer to a given query graph (i.e. information need) if it is not present in one single source, is not investigated. In this paper, we try to highlight the potential and the motivation that lies behind the graph aggregation query problem.We propose a first approach to support aggregated search in graph databases. We discuss the preliminary results from the algorithmic point of view.