Department of Computer Science

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/16

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Author: search.filters.author.Dr. Abid Sohail BhuttaSubject: search.filters.subject.FA18

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    Process Model Generation from Textual Descriptions
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Aleena Nazir; FA18-RCS-014; LHR TP 7290; Dr. Abid Sohail Bhutta
    Process models are an important source to gather the information on organizational workflows and also represent the first point of process analysis and improvement. In organizations, business process modeling is an important tool to understand and automate the business processes. However, in many organizations the existing documentation of business processes is difficult to understand by the analyst. So, in real-life organizations, the high complexity of business processes is constantly raising an issue. Due to this, the establishment of process models for the business process is becoming a challenge for the stakeholders. So, the process model extraction from the business processes may helpful to minimize the process modeling effort. But, manual generation of business process models is a time taking task for the stakeholders. Yet, to assist this task, new methods can be implemented for the automation of process design phase. An approach to generate process models from the textual descriptions has been developed. In this approach, we use different natural language processing techniques to define a set of mapping rules. Through these mapping rules, we extract the elements business process models from textual descriptions and also checked the correct sequence of extracted elements for business process models. By combining the business process elements according to their sequence, process model is generated
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    On Enhancing the Quality of Business Process Model’s Activities Labels
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Urooj Fatima; FA18-RCS-006; LHR TP 7291; Dr. Abid Sohail Bhutta
    Business process models describe their operations, events, and control flows through graphical illustrations to increase the knowledge and awareness of business processes. Large corporations use models to document and design business processes. With the growing number of business process models and trained modelers, modeling initiatives demand quality assurance. Nevertheless, checking the quality of the process model, especially its activity labels, is a challenge. In labels, synonymy, vagueness, homonymy, incorrect labeling, as well as different modeling styles result in ambiguity, uncertainty, and misunderstandings. Quality of activity labels rely on precise and fitful words which are according to the domain process models taking quality parameters under consideration. The problem arises when the activity labels are too short and provide limited information and words facing the zero-derivation problem. For this purpose, algorithms have been deployed which will recognize, identify and check the labeling styles of a process model. Activity labels has been extracted automatically. Further, NLP techniques like WordNet has been used for the analysis of activity labels. In this study, the quality of textual labels in activities of a process models is addressed. Activity labels has been analyzed using a collection of business process models based on medical chronic diseases. Results obtained by deployment of algorithms on automatically extracted labels confirms the applicability and accuracy of proposed techniques.