International Journal of Computer Science and Mobile Computing (IJCSMC)

Source ID:00000069
Volume 7, Issue 4,April 2018, Pages 191-194, Page Count - 4

Study and Analysis of Infrequent Behaviour Patterns in Business Process Event Logs

S.Santhoshkumar (1) K.Silambarasi (2) E.Ramaraj (3)

(1) Department of Computer Science, Alagappa University, Karaikudi, India.
(2) Department of Computer Science, Alagappa University, Karaikudi, India.
(3) Department of Computer Science, Alagappa University, Karaikudi, India.

Manuscript ID:- 00000-70790
Access Type : Open Access
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Cite this article:S.Santhoshkumar,K.Silambarasi,E.Ramaraj,  Study And Analysis Of Infrequent Behaviour Patterns In Business Process Event Logs, International Journal of Computer Science and Mobile Computing(IJCSMC), 2018, 7(4), PP.191-194

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Abstract

Data Mining consists of variety of techniques. Association rule mining is one of the familiar techniques used to solve many real world problems like market basket analysis, marketer prediction. The dynamic data mining is a new phenomenon used to handle event log information. It is highly used for business applications. The frequent item set mining with association rules gives better results with process log data. But least frequent items affect the performance rate of business transactions. In order reduce the noise and least significant items, filtering techniques are used. This paper is aimed to remove infrequent behavior from event logs.
Author Keywords
Data Mining Association Rule Mining Infrequent Patterns filtering Event logs


ISSN Print: ISSN Online: 2320-088X
Source Type: Journals Document Type: Journal Article
Publication Language: English DOI:
Abbreviated Journal Title: IJCSMC Access Type: Open Access
Publisher Name: ZAIN Publications Resource Licence: CC BY-NC
Major Subject:Physical Sciences Subject Area classification: Computer Science
Subject area: Computer Vision and Pattern Recognition Source: SCOPEDATABASE