Chapter

Bisociative Knowledge Discovery

Volume 7250 of the series Lecture Notes in Computer Science pp 263-284

Open Access This content is freely available online to anyone, anywhere at any time.

Towards Discovery of Subgraph Bisociations

  • Uwe NagelAffiliated withNycomed-Chair for Bioinformatics and Information Mining, Dept. of Computer and Information Science, University of Konstanz
  • , Kilian ThielAffiliated withNycomed-Chair for Bioinformatics and Information Mining, Dept. of Computer and Information Science, University of Konstanz
  • , Tobias KötterAffiliated withNycomed-Chair for Bioinformatics and Information Mining, Dept. of Computer and Information Science, University of Konstanz
  • , Dawid PiątekAffiliated withNycomed-Chair for Bioinformatics and Information Mining, Dept. of Computer and Information Science, University of Konstanz
  • , Michael R. BertholdAffiliated withNycomed-Chair for Bioinformatics and Information Mining, Dept. of Computer and Information Science, University of Konstanz

Abstract

The discovery of surprising relations in large, heterogeneous information repositories is gaining increasing importance in real world data analysis. If these repositories come from diverse origins, forming different domains, domain bridging associations between otherwise weakly connected domains can provide insights into the data that are not accomplished by aggregative approaches. In this paper, we propose a first formalization for the detection of such potentially interesting, domain-crossing relations based purely on structural properties of a relational knowledge description.