@article{2009-SteeringLearningDistance-CACM
, author={Frank Nielsen}
, title={Steering self-learning distance algorithms}
, journal={Communications of the ACM}
, month={November}
, year={2009}
, volume={52}
, number={11}
, pages={VE}
, doi={10.1145.1592761}
, abstract={
  The concept of distance expresses the distortion measure between any pair of entities
 lying in a common space.  Distances are ubiquitous in computational science. We
 concisely review the role and recent development of distance families in computer
 science. Nowadays, the most appropriate distance functions of complex high-dimensional
 data sets cannot anymore be guessed manually and hard-coded, but rather need to
 be fully automatically learnt, or even better partially user-steered for personalization.
 We envision a whole new generation of personalized information retrieval systems
 incorporating self-learning built-in distance modules, and providing user interfaces
 to better take into considerations users/groups subjective tastes.}
}