REVIEWONTODEVELOPIMPROVEMETHODSFORBUSINESSPROCESS MODELING USING DATA MINING

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Published Dec 27, 2024

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Priyanka ,
Studentat, Department of Computer Science and Engineering, BDCOE, Sevagram, Wardha, Maharashtra, India.
Dr. Sudhir W. Mohod
Professor & HOD, Department of Computer Science and Engineering, BDCOE, Sevagram, Wardha, Maharashtra, India.

Abstract

In contemporary business, the ability to effectively and efficiently model business processes for firms is necessary due to the regular modifications of custom demands as well as the specialization of business processes. Workflow mining and process retrieval, two conventional techniques for enhancing business process modeling, never the less need a lot of manual labor. One method used in data mining to divideadatasetintogroupsis clustering. Several method sareemployedtogroup the data, compute the measure, and then reassign the data until the measured measures remain constant, indicating a stable segment. Here clustering method is used in data mining to divide a dataset into group .The current search engines are unable to offer visitors or tourists a tailored answer when they are looking for information about a city's transportation options, tourist attractions, shops, places of visit, hotel options, restaurant information, etc. Therefore, in order to facilitate travelers or a visitor, a Revolutionizing business process modeling with data mining innovation is crucial. This system should be able to quickly and effectively deliver information about things to buy in a location, such hotel options. In this review, we have attempted to The Revolutionizing business process modeling with data mining innovation is a prototype system. Abstract has created in a Hadoop environment. Abstract also proposes the architecture for the Revolutionizing business process modeling.

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Issue
Vol 11 No 12 (2024): Volume 11 Issue 12
Section
Articles

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