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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nowozin, S. Tsuda, K. |
| Copyright Year | 2008 |
| Description | Author affiliation: Max Planck Inst. for Biol. Cybern., Tubingen (Nowozin, S.; Tsuda, K.) |
| Abstract | Discovery of knowledge from geometric graph databases is of particular importance in chemistry and biology, because chemical compounds and proteins are represented as graphs with 3D geometric coordinates. In such applications, scientists are not interested in the statistics of the whole database. Instead they need information about a novel drug candidate or protein at hand, represented as a query graph. We propose a polynomial-delay algorithm for geometric frequent subgraph retrieval. It enumerates all subgraphs of a single given query graph which are frequent geometric epsi-subgraphs under the entire class of rigid geometric transformations in a database. By using geometric epsi-subgraphs, we achieve tolerance against variations in geometry. We compare the proposed algorithm to gSpan on chemical compound data, and we show that for a given minimum support the total number of frequent patterns is substantially limited by requiring geometric matching. Although the computation time per pattern is larger than for non-geometric graph mining, the total time is within a reasonable level even for small minimum support. |
| Starting Page | 953 |
| Ending Page | 958 |
| File Size | 584330 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769535029 |
| ISSN | 15504786 |
| DOI | 10.1109/ICDM.2008.38 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-15 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Information retrieval Spatial databases Chemical compounds Proteins Chemistry Statistics Drugs Polynomials Geometry Pattern matching geometric patterns geometric graph mining frequent graph mining |
| Content Type | Text |
| Resource Type | Article |
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