Eurofuse 2011 pp 257-268 | Cite as

Learning Valued Relations from Data

  • Willem Waegeman
  • Tapio Pahikkala
  • Antti Airola
  • Tapio Salakoski
  • Bernard De Baets
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 107)


Driven by a large number of potential applications in areas like bioinformatics, information retrieval and social network analysis, the problem setting of inferring relations between pairs of data objects has recently been investigated quite intensively in the machine learning community. To this end, current approaches typically consider datasets containing crisp relations, so that standard classification methods can be adopted. However, relations between objects like similarities and preferences are in many real-world applications often expressed in a graded manner. A general kernel-based framework for learning relations from data is introduced here. It extends existing approaches because both crisp and valued relations are considered, and it unifies existing approaches because different types of valued relations can be modeled, including symmetric and reciprocal relations. This framework establishes in this way important links between recent developments in fuzzy set theory and machine learning. Its usefulness is demonstrated on a case study in document retrieval.


Domain Knowledge Social Network Analysis Kronecker Product Reciprocal Relation Reproduce Kernel Hilbert Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Willem Waegeman
    • 1
  • Tapio Pahikkala
    • 2
  • Antti Airola
    • 2
  • Tapio Salakoski
    • 2
  • Bernard De Baets
    • 1
  1. 1.KERMIT, Department of Applied Mathematics, Biometrics and Process ControlGhent UniversityGhentBelgium
  2. 2.Department of Information Technology and the Turku Centre for Computer ScienceUniversity of TurkuTurkuFinland

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