2
Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka
3
Open University Malaysia
Abstract
In this study, a hierarchical temporal memory modeling is implemented. The study is based on the classifying processes in multi-set event logs. The Hierarchical Temporal Memory (HTM) learning algorithms that handle sparse representation of data and online learning were used to build the model. The framework exhibits potency in process discovery. Every organization has set goals to achieve which could span from delivery of services to end users, transformation of unrefined materials into a desired product, rendering of support service to guarantee clients satisfaction, recording of financial transactions for the purpose of budgeting and management amongst others [1]. The accomplishments and achievements of these objectives and aim require the presence of an activity or a task, or perhaps, multiple activities and tasks. These set of tasks and activities are logically related and flow in a logical manner and are termed business processes. Business process is all about the daily operations of organizations and businesses irrespective of the business domain or industry they operate in. It can further be defined as a way of specifying the approach in which the resources of an enterprise are used [2].
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