Multi-level Utility Mining: Retrieval of High Utility Itemsets in a Transaction Database. (June 2019)

• Record Type: Journal Article
• Authors: Sivamathi, C; Vijayarani, S
• Is Part Of: Computers & electrical engineering. Volume 76(2019)
• Page Start: 268
• Page End: 282
• Publication Date: 2019-06
• Subjects: Utility mining -- Multi-level utility mining -- Multi-level high utility itemsets -- Multiple minimum utility threshold -- Multilevel utility mining tree; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.04.003
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Utility mining is a key field in data mining, meant to reveal high utility itemsets (HUIs). It retrieves HUIs from a multi-level dataset. An algorithm MUMA (multilevel utility mining algorithm) was proposed to retrieve HUIs in a multi-level dataset. MUM algorithm implements a tree structure, called MUMT (multilevel utility mining tree), to store utility information of the itemsets. Several enhanced tree-based algorithms namely multi-level utility mining using enumeration tree (MU_ET), multi-level utility mining using utility pattern tree (MU_UP), multi-level utility mining using lexicographic tree (MU_LG) are also analysed. MUMA was compared with MU_ET, MU_UP and MU_LG. The experiments are performed using different datasets like transaction datasets, weblogdatasets, and synthetic datasets.