Yongwang Yuan¹, Xiangwei Liu^2,3,*, Ke Lu^1,3

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1227-1252, 2024, DOI:10.32604/cmc.2023.046937 - 30 January 2024

Abstract Predictive Business Process Monitoring (PBPM) is a significant research area in Business Process Management (BPM) aimed at accurately forecasting future behavioral events. At present, deep learning methods are widely cited in PBPM research, but no method has been effective in fusing data information into the control flow for multi-perspective process prediction. Therefore, this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data fusion. Firstly, the first layer BERT network learns the correlations between different category attribute data. Then, the attribute data is integrated into a weighted event-level feature vector and More >

Jiwon Jeon, Junho Kim, Mincheol Shin, Mucheol Kim^*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3403-3421, 2023, DOI:10.32604/csse.2023.036658 - 03 April 2023

Abstract The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment. However, while collaborative business expands the realm of businesses, it also causes various hazards in collaborative Interaction, such as data falsification, inconstancy, and misuse. To solve these issues, a blockchain-based collaborative business modeling approach was proposed and analyzed. However, the existing studies lack the blockchain risk problem-solving specification, and there is no verification technique to examine the process. Consequently, it is difficult to confirm the appropriateness of the approach. Thus, here, we propose and… More >

Faizan Ahmed Khan¹, Farooq Ahmad¹, Arfat Ahmad Khan², Chitapong Wechtaisong^2,*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2019-2032, 2023, DOI:10.32604/csse.2023.023490 - 01 August 2022

Abstract The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data. This data can be extremely valuable for executing organizations because the data allows constant monitoring, analyzing, and improving the underlying processes, which leads to the reduction of cost and the improvement of the quality. Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours. This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals… More >

Farzana Kausar Gondal^1,*, Syed Khuram Shahzad², Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1369-1386, 2023, DOI:10.32604/iasc.2023.028407 - 19 July 2022

Abstract Cities are facing challenges of high rise in population number and consequently need to be equipped with latest smart services to provide luxuries of life to its residents. Smart integrated solutions are also a need to deal with the social and environmental challenges, caused by increasing urbanization. Currently, the development of smart services’ integrated network, within a city, is facing the barriers including; less efficient collection and sharing of data, along with inadequate collaboration of software and hardware. Aiming to resolve these issues, this paper recommended a solution for a synchronous functionality in the smart… More >

Abid Sohail¹, Ammar Haseeb¹, Mobashar Rehman^2,*, Dhanapal Durai Dominic³, Muhammad Arif Butt⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3603-3618, 2021, DOI:10.32604/cmc.2021.017795 - 24 August 2021

Abstract There are numerous application areas of computing similarity between process models. It includes finding similar models from a repository, controlling redundancy of process models, and finding corresponding activities between a pair of process models. The similarity between two process models is computed based on their similarity between labels, structures, and execution behaviors. Several attempts have been made to develop similarity techniques between activity labels, as well as their execution behavior. However, a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between More >

Abid Sohail^1,*, Dhanapal Durai Dominic², Mohammad Hijji³, Muhammad Arif Butt⁴

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1141-1157, 2021, DOI:10.32604/cmc.2021.018023 - 04 June 2021

Abstract Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge. One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process. However, evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way, is missing. It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored. To address this More >

Abid Sohail^1,*, Khurram Shahzad², P. D. D. Dominic³, Muhammad Arif Butt², Muhammad Arif⁴, Muhammad Imran Tariq⁵

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 303-319, 2021, DOI:10.32604/cmc.2021.014201 - 12 January 2021

Abstract Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service. Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task. In continuation of our previous work, we categorize resources into human and non-human resources. For instance, in the healthcare domain, human resources include doctors, nurses, and other associated staff responsible for the execution of healthcare activities; whereas the non-human resources include surgical and other equipment needed for execution. In this study, we contend that… More >

Ahmad Alomari^1,∗, Alain April¹, Carlos Monsalve², Amjad Gawanmeh³

Computer Systems Science and Engineering, Vol.33, No.3, pp. 219-227, 2018, DOI:10.32604/csse.2018.33.219

Abstract Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process More >