An Experimental on Top-k High Utility Itemset Mining By Efficient Algorithm Tkowithtku.
Ashwini Kurhade1, J. Naveenkumar2, A. K. Kadam3
1Ashwini Kurhade, Department of Computer Engineering, Bharati Vidyapeeth Deemed to be University College of Engineering, Pune, India.
2Prof. Dr. J. Naveenkumar, Faculty of Computer Engineering, Bharati Vidyapeeth Deemed to be University College of Engineering, Pune, India.
3Dr. A. K. Kadam3 Faculty of Computer Engineering, Bharati Vidyapeeth Deemed to be University College of Engineering, Pune, India.
Manuscript received on 09 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 08 July 2019 | PP: 519-522 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H11180688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The manufacturer’s decision to make the top-of – the-high utility item sets (HUI) mining issue more flexible, the perception of item utility, and the number of patterns that are desired. This completes the decision maker’s requirement to use the trial and error method to determine the suitable minimum utility threshold value. Top -K HUI mining issue, however, is more difficult and needs strategic enhancement approaches to be used effectively. Few approaches have been proposed to this literature to improve effectiveness in HUI mining.
Keywords: Utility mining, data mining, top-of-high utility item sets, TKO, TKU
Scope of the Article: Data Mining