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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chandra, B. Bhaskar, S. |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Mathematics, Indian Institute of Technology, Hauz Khas, New Delhi-110016, India (Chandra, B.) || Amarnath and Sashi Khosla School of Information Technology, Indian Institute of Technology, Hauz Khaz, New Delhi-110016, India (Bhaskar, S.) |
| Abstract | Mining frequent substructures has gained importance in the recent past. Number of algorithms has been presented for mining undirected graphs. Focus of this paper is on mining frequent substructures in directed labeled graphs since it has variety of applications in the area of biology, web mining etc. A novel approach of using equivalence class principle has been proposed for reducing the size of the graph database to be processed for finding frequent substructures. For generating candidate substructures a combination of L-R join operation, serial and mixed extensions have been carried out. This avoids missing of any candidate substructures and at the same time candidate substructures that have high probability of becoming frequent are generated. |
| Starting Page | 988 |
| Ending Page | 995 |
| File Size | 523165 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424496358 |
| ISSN | 21614407 |
| e-ISBN | 9781424496372 |
| DOI | 10.1109/IJCNN.2011.6033330 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Databases Approximation algorithms Data mining Vegetation Complexity theory Computer aided manufacturing |
| Content Type | Text |
| Resource Type | Article |
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