Abstrait

Mining Association Rules from Infrequent Itemsets: A Survey

Diti Gupta, Abhishek Singh Chauhan

Association Rule Mining (AM) is one of the most popular data mining techniques. Association rule mining generates a large number of rules based on support and confidence. However, post analysis is required to obtain interesting rules as many of the generated rules are useless.However, the size of the database can be very large. It is very time consuming to find all the association rules from a large database, and users may be only interested in the associations among some items.So mining association rules in such a way that we maximize the occurrences of useful pattern. In this paper we study several aspects in this direction and analyze the previous research.So that we come with the advantages and disadvantages.

Avertissement: Ce résumé a été traduit à l'aide d'outils d'intelligence artificielle et n'a pas encore été examiné ni vérifié

Indexé dans

Academic Keys
ResearchBible
CiteFactor
Cosmos IF
RefSeek
Hamdard University
World Catalogue of Scientific Journals
Scholarsteer
International Innovative Journal Impact Factor (IIJIF)
International Institute of Organised Research (I2OR)
Cosmos

Voir plus