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Summary form only given. Recently, an emerging trend of representing objects by graphs can be observed. As a matter of fact, graphs offer a versatile alternative to feature vectors in many subfields of intelligent information processing, including pattern recognition, machine learning, and data mining. However, the space of graphs contains almost no mathematical structure, and consequently, there...
In pattern recognition and related fields, graph-based representations offer a versatile alternative to the widely used feature vectors. Therefore, an emerging trend of representing objects by graphs can be observed. This trend is intensified by the development of novel approaches in graph-based machine learning, such as graph kernels or graph-embedding techniques. These procedures overcome a major...
Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for instance, how to obtain a representative of a set of graphs. The median graph has been defined for that purpose, but existing algorithms are computationally complex and have a very limited applicability. In this paper we propose...
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