Jiang, Chuntao
(2011)
Frequent subgraph mining algorithms on weighted graphs.
PhD thesis, University of Liverpool.
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Abstract
This thesis describes research work undertaken in the field of graph-based knowledge discovery (or graph mining). The objective of the research is to investigate the benefits that the concept of weighted frequent subgraph mining can offer in the context of the graph model based classification. Weighted subgraphs are graphs where some of the vertexes/edges are considered to be more significant than others. How to discover frequent sub-structures with different strengths is the main issue to be resolved in this thesis. The main approach to addressing this issue is to integrate weight constraints into the frequent subgraph mining process. It is suggested that the utilization of weighted frequent subgraph mining generates more discriminate and significant subgraphs, which will have application in, for example, the classification and clustering of graph data.
| Item Type: | Thesis (PhD) |
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| Depositing User: | Symplectic Admin |
| Date Deposited: | 19 Oct 2023 17:54 |
| Last Modified: | 19 Oct 2023 17:57 |
| DOI: | 10.17638/03174313 |
| Copyright Statement: | Copyright © and Moral Rights for this thesis and any accompanying data (where applicable) are retained by the author and/or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3174313 |
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