Stellar mass black hole optimisation for utility mining. (9th July 2019)

• Record Type: Journal Article
• Authors: Kannimuthu, Subramanian; Premalatha, Kandhasamy
• Is Part Of: International journal of data analysis techniques and strategies. Volume 11:Number 3(2019)
• Page Start: 222
• Page End: 245
• Publication Date: 2019-07-09
• Subjects: data mining -- genetic algorithm -- stellar mass black hole optimisation -- SBO -- high utility itemsets -- utility mining; Electronic data processing -- Periodicals; Database searching -- Periodicals; 005
• Languages: English
• ISSNs: 1755-8050

Abstract

Major challenges in mining high utility itemsets from the transaction databases requires exponential search space and database-dependent minimum utility threshold. The search space is very large because of the large number of distinct items and size of the database. Data analysts need to specifying appropriate minimum utility thresholds for their data mining tasks though they may have no knowledge pertaining to their databases. To get rid of these problems, Stellar mass black hole optimisation (SBO) method is proposed to mine Top-K HUIs from the transaction database without specifying minimum utility threshold. To know the performance of SBO, the experiment results are compared with GA.