IDA - Intelligent Data Analysis Research Group

BibTeX Entry

@inproceedings{zakova.planlearn.2008,
  category = {ida-publications},
  author = {Monika {\v Z}{\'a}kov{\'a} and Petr K{\v r}emen and Filip {\v Z}elezn{\'y} and Nada Lavra{\v c}},
  title = {Planning to Learn with a Knowledge Discovery Ontology},
  booktitle = {Planning to Learn Workshop (PlanLearn 2008) at ICML 2008},
  year = {2008},
  keywords = {planning, machine learning},
  abstract = {This paper addresses the problem of semi-automatic design of workflows for complex knowledge discovery tasks. Assembly of optimized knowledge discovery workflows requires awareness of and extensive knowledge about the principles and mutual relations between diverse data processing and mining algorithms. We aim at alleviating this burden by automatically proposing workflows for the given type of inputs and required outputs of the discovery process. The methodology adopted in this study is to define a formal conceptualization of knowledge types and data mining algorithms and design a planning algorithm, which extracts constraints from this conceptualization for the given user's input-output requirements. We demonstrate our approach in two use cases, one from scientific discovery in genomics and another from advanced engineering.},
  vvvs = {1},
  obory = {JC, JD},
  projnum = {12-05001/13133 , 80-06002/13133},
  projects = {ML/BIO, SEVENPRO},
}


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