Subgraph Mining

Author:

Fischer Ingrid1,Meinl Thorsten1

Affiliation:

1. Friedrich-Alexander University Erlangen-Nürnberg, Germany

Abstract

The amount of available data is increasing very fast. With this data the desire for data mining is also growing. More and larger databases have to be searched to find interesting (and frequent) elements and connections between them. Most often, the data of interest is very complex. It is common to model complex data with the help of graphs consisting of nodes and edges that often are labeled to store additional information. Applications can be found in very different fields. For example, the two-dimensional structure of molecules often is modeled as graphs having the atoms as nodes and bonds as edges. The same holds for DNA or proteins. Web pages and links between Web pages also can be represented as graph. Other examples are social networks as citation networks and CAD circuits; graphs can be found in a lot of different application areas.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Quantitative Comparison of the Subgraph Miners MoFa, gSpan, FFSM, and Gaston;Knowledge Discovery in Databases: PKDD 2005;2005

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