Bisociative Knowledge Discovery

Volume 7250 of the series Lecture Notes in Computer Science pp 438-451

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

Bisociative Exploration of Biological and Financial Literature Using Clustering

  • Oliver SchmidtAffiliated withUniversity of Ulster
  • , Janez KranjcAffiliated withJozef Stefan Institute
  • , Igor MozetičAffiliated withJozef Stefan Institute
  • , Paul ThompsonAffiliated withUniversity of Ulster
  • , Werner DubitzkyAffiliated withUniversity of Ulster


The bile acid and xenobiotic system describes a biological network or system that facilitates detoxification and removal from the body of harmful xenobiotic and endobiotic compounds. While life scientists have developed a relatively comprehensive understanding of this system, many mechanistic details are yet to be discovered. Critical mechanisms are those which are likely to significantly further our understanding of the fundamental components and the interaction patterns that govern this systems gene expression and the identification of potential regulatory nodes. Our working assumption is that a creative information exploration of available bile acid and xenobiotic system information could support the development (and testing) of novel hypotheses about this system. To explore this we have set up an information space consisting of information from biology and finance, which we consider to be two semantically distant knowledge domains and therefore have a high potential for interesting bisociations. Using a cross-context clustering approach and outlier detection, we identify bisociations and evaluate their value in terms of their potential as novel biological hypotheses.


Clustering outlier detection bisociative information exploration