Median graph computation by means of graph embedding into vector spaces

Miquel Ferrer, Itziar Bardají, Ernest Valveny, Dimosthenis Karatzas, Horst Bunke, Yun Fu (Editor), Yunqian Ma (Editor)

Research output: Chapter in BookChapterResearchpeer-review

4 Citations (Scopus)


© Springer Science+Business Media New York 2013. In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant.
Original languageEnglish
Title of host publicationGraph Embedding for Pattern Analysis
Place of PublicationDordrecht (NL)
Number of pages26
Publication statusPublished - 1 Jan 2013


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