DMA: Matrix Based Dynamic Itemset Mining Algorithm
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Igi Global
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Updates on an operational database bring forth the challenge of keeping the frequent itemsets up-to-date without re-running the itemset mining algorithms. Studies on dynamic itemset mining, which is the solution to such an update problem, have to address some challenges as handling i) updates without re-running the base algorithm, ii) changes in the support threshold, iii) new items and iv) additions/deletions in updates. The study in this paper is the extension of the Incremental Matrix Apriori Algorithm which proposes solutions to the first three challenges besides inheriting the advantages of the base algorithm which works without candidate generation. In the authors' current work, the authors have improved a former algorithm as to handle updates that are composed of additions and deletions. The authors have also carried out a detailed performance evaluation study on a real and two benchmark datasets.
Açıklama
Anahtar Kelimeler
Algorithms, Dynamic Itemset Mining, Itemset Mining, Matrix Apriori, Operational Database
Kaynak
International Journal of Data Warehousing and Mining
WoS Q Değeri
Q3
Scopus Q Değeri
Cilt
9
Sayı
4
