Structuring depth-first search algorithms in Haskell
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
The uncertain reasoner's companion: a mathematical perspective
The uncertain reasoner's companion: a mathematical perspective
Data Mining the Yeast Genome in a Lazy Functional Language
PADL '03 Proceedings of the 5th International Symposium on Practical Aspects of Declarative Languages
An Alternative View of Knowledge Discovery
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
Inductive graphs and functional graph algorithms
Journal of Functional Programming
wxHaskell: a portable and concise GUI library for haskell
Haskell '04 Proceedings of the 2004 ACM SIGPLAN workshop on Haskell
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Modelling conditional knowledge discovery and belief revision by abstract state machines
ASM'03 Proceedings of the abstract state machines 10th international conference on Advances in theory and practice
An approach to learning relational probabilistic FO-PCL knowledge bases
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
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While declarative programming languages are often considered to be applicable to “toy problems” only, we present an example of a real-world programming task realized with a functional programming language. CondorCKD is a novel algebraic knowledge discovery algorithm completely implemented in Haskell. We give an overview of CondorCKD and describe our experiences gained during its development, including the implementation of a graphical user interface and a novel approach to compute the cycles of an undirected graph.