Pushing Fuzzy Constraints in Frequent Itemset Mining

Autor:	Qiang Zhang, Zhi-bo Ren
Rok vydání:	2006
Předmět:	Apriori algorithm Focus (computing) Fuzzy set InformationSystems_DATABASEMANAGEMENT computer.software_genre Fuzzy logic ComputingMethodologies_PATTERNRECOGNITION Knowledge extraction Fuzzy set operations Pruning (decision trees) Data mining Constraint (mathematics) computer Mathematics
Zdroj:	2006 International Conference on Machine Learning and Cybernetics.
DOI:	10.1109/icmlc.2006.258707
Popis:	Human is the focus of knowledge discovery. The user can express his focus via constraints in mining. However, constraints specified by the user are often fuzzy. The paper proposes the notion of fuzzy constraints and develops techniques to introduce these fuzzy constraints into the Apriori algorithm for mining frequent itemsets. The experiment results show the effectiveness of the improved techniques.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7990848a74ba2909a22640e72b4c9e0f https://doi.org/10.1109/icmlc.2006.258707 Zobrazit plný text záznamu