Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Efficient parallel data mining for association rules
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Scalable parallel data mining for association rules
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The bits between the lambdas: binary data in a lazy functional language
Proceedings of the 1st international symposium on Memory management
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Genome scale prediction of protein functional class from sequence using data mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Parallel data mining for association rules on shared memory systems
Knowledge and Information Systems
Efficient Mining of Association Rules in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Methods and Problems in Data Mining
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Improving the efficiency of inductive logic programming through the use of query packs
Journal of Artificial Intelligence Research
Proceedings of the 2005 ACM symposium on Applied computing
Gene classification: issues and challenges for relational learning
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
CARIBIAM: Constrained Association Rules using Interactive Biological IncrementAl Mining
International Journal of Bioinformatics Research and Applications
Parallel ILP for distributed-memory architectures
Machine Learning
Background Knowledge Enriched Data Mining for Interactome Analysis
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Intelligent Data Analysis - Ubiquitous Knowledge Discovery
Outlier detection in relational data: A case study in geographical information systems
Expert Systems with Applications: An International Journal
Strategies to parallelize ILP systems
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Algebraic knowledge discovery using haskell
PADL'07 Proceedings of the 9th international conference on Practical Aspects of Declarative Languages
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Critics of lazy functional languages contend that the languages are only suitable for toy problems and are not used for real systems. We present an application (PolyFARM) for distributed data mining in relational bioinformatics data, written in the lazy functional language Haskell. We describe the problem we wished to solve, the reasons we chose Haskell and relate our experiences. Laziness did cause many problems in controlling heap space usage, but these were solved by a variety of methods. The many advantages of writing software in Haskell outweighed these problems. These included clear expression of algorithms, good support for data structures, abstraction, modularity and generalisation leading to fast prototyping and code reuse, parsing tools, profiling tools, language features such as strong typing and referential transparency, and the support of an enthusiastic Haskell community. PolyFARM is currently in use mining data from the Saccharomyces cerevisiae genome and is freely available for non-commercial use at http://www.aber.ac.uk/compsci/Research/bio/dss/polyfarm/.