Please use this identifier to cite or link to this item: http://openarchive.nure.ua/handle/document/3688
Title: Модель знание-емкого бизнес-процесса для задач интеллектуального анализа процессов
Authors: Левыкин, В. М.
Чалая, О. В.
Keywords: знание-емкий бизнес-процесс
модель
интеллектуальный анализ
темпоральные правила
Issue Date: 2016
Citation: Левыкин В. М., Чалая О. В. Модель знание-емкого бизнес-процесса для задач интеллектуального анализа процессов // Управляющие системы и машины. – 2016. - № 6. – С. 59-66.
Abstract: Запропоновано модель знання-ємного бізнес-процесу, яка містить набір його станів і правила переходів між ними. Модель відрізняється від існуючих тим, що пов'язує контекст і послідовність дій процесу за допомогою темпоральних правил, що дозволяє адаптувати модель під час виконання бізнес-процесу шляхом включення нових правил. The concept drift problem of knowledge-intensive business process is considered. The problem lies in the fact that knowledge workers use their personal knowledge to change the workflow during its execution. They take into account the context of the process to change the workflow. The result is a complex structure of the workflow. That is why, for managing the business process, it is important to include knowledge that makes the concept drift in the process model. It gives the opportunity to make the process model more adequate to the real knowledge intensive business processes. So, the purpose of this paper is development of process model that includes the description of the process context, the workflow and the knowledge. That knowledge is used to choose an activity of a workflow in the specific context. Model of knowledge-intensive business process for process mining is proposed. The model includes a set of states of a business process and a set of transition rules. State of the business process is defined by a set of attributes of objects that uses the business process. The relation of the transition between the states is determined by the logical rules. These rules define the possible workflows in accordance with the various conditions of the business process context. The model differs from the existing ones by linking the context and workflow through the logical rules. This makes it possible to adapt the model of business process at runtime by integrating the new rules. The model is designed to create a description of complex knowledge intensive processes using process mining techniques. Process mining techniques use the event logs to build a process model. State of the business process in the event logs is defined by a set of attributes of the events that belong to the log. We can use a subset of the event log for problems of process mining to build an interesting fragment of the proposed process model. This subset is defined by a set of pre-defined event attributes. These attributes belong to the events, and to a priori defined subset of objects that belongs to the context of the process. This allows to avoid building a spaghetti-like workflows.
URI: http://openarchive.nure.ua/handle/document/3688
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