| Submission declined on 21 September 2024 by Johannes Maximilian (talk). This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources.
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
Once you save your changes using the "Publish changes" button below, you will be able to resubmit your draft for review by pressing the "Resubmit" button that will appear here. |  |
Graph difference or Structural difference is defined as a measure of the number of modifications required to transform an input graph into another.[1] Graph difference is not unique and depends upon the distance measure used. Distance Measures proposed for computing graph difference include Gernet distance[2], Graph edit distance[3], and Wasserstein distance[4].
Problem of computing graph difference is equivalent to computing the Maximum Common Subgraph and is NP-Complete.[5]
- ^ Shapiro, Linda G.; Haralick, Robert M. (1981). "Structural Descriptions and Inexact Matching". IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-3 (5): 504–519. doi:10.1109/TPAMI.1981.4767144. ISSN 0162-8828. PMID 21868971.
- ^ Gernet, Dieter (1979). "Measuring the similarity of complex structures by means of graph grammars". Bulletin of the European Association of Theoretical Computer Science (EATCS) (7): 3–9.
- ^ Sanfeliu, Alberto; Fu, King-Sun (1983). "A distance measure between attributed relational graphs for pattern recognition". IEEE Transactions on Systems, Man, and Cybernetics. SMC-13 (3): 353–362. doi:10.1109/TSMC.1983.6313167. ISSN 0018-9472.
- ^ Han, Yuehui; Hui, Le; Jiang, Haobo; Qian, Jianjun; Xie, Jin (2022). "Generative Subgraph Contrast for Self-Supervised Graph Representation Learning". In Avidan, Shai; Brostow, Gabriel; Cissé, Moustapha; Farinella, Giovanni Maria; Hassner, Tal (eds.). Computer Vision – ECCV 2022. Lecture Notes in Computer Science. Vol. 13690. Cham: Springer Nature Switzerland. pp. 91–107. doi:10.1007/978-3-031-20056-4_6. ISBN 978-3-031-20056-4.
- ^ Bunke, H. (1997-08-01). "On a relation between graph edit distance and maximum common subgraph". Pattern Recognition Letters. 18 (8): 689–694. Bibcode:1997PaReL..18..689B. doi:10.1016/S0167-8655(97)00060-3. ISSN 0167-8655.