Practise Mining to Predict Type of Client Performence
C. Nalini1, R. Kavitha2, G. Kavitha3, S. Sangeetha4
1C. Nalini , Department of computer science engineering, Bharath Institute of Higher Education and Research, Chennai, Tamilnadu, India.
2R. Kavitha, Department of CSE, Bharath Institute of Higher Education and Research, Chennai, Tamilnadu, India.
3G. Kavitha, Assistant Professor, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India.
4S. Sangeetha, Department of CSE, Bharath Institute of Higher Education and Research, Chennai, Tamilnadu, India.
Manuscript received on 07 July 2019 | Revised Manuscript received on 19 July 2019 | Manuscript Published on 23 August 2019 | PP: 964-968 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I32050789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3205.0789S319
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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 aim of process mining implement is firstly to discover the typical customer fulfillment business process-process mining act as a bridge between data mining and web mining. Process mining in an active innovative research area in recent year. The goal is to be extract process –related information from the event log by observing events recorded by some of the information system using the click stream method. Finally we are classifying the different categories of customer behavior using weka tool after we applied the knowledge miner. The result provides to find the different type of customer and their behavior and its helps the company to improve the product and satisfied customer needs.
Keywords: Data mining, Naïve bayes, IBK, J48
Scope of the Article: Data Mining