Abstract
Pattern mining problems are useful in many applications. Due to a common theoretical background for such problems, generic concepts can be re-used to easier the development of algorithms. As a consequence, these problems can be implemented with only minimal effort, i.e. programmers do not have to be aware of low-level code, customized data structures and algorithms being available for free. A toolkit, called iZi, has been devised and applied to several problems such as itemset mining, constraint mining in relational databases and query rewriting in data integration systems. According to our first results, the programs obtained using our library offer a very good tradeoff between performances and development simplicity.
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Flouvat, F., De Marchi, F., Petit, JM. (2008). iZi: A New Toolkit for Pattern Mining Problems. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds) Foundations of Intelligent Systems. ISMIS 2008. Lecture Notes in Computer Science(), vol 4994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68123-6_14
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DOI: https://doi.org/10.1007/978-3-540-68123-6_14
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