This workshop will be organized under the auspices of BTIIC (BT Ireland Innovation Centre), a research partnership between Ulster University and BT. Projects undertaken by BTIIC integrate theoretical principles with industrial practice to address a range of complex data mining and machine learning problems in the telecommunications sector. One such area is smart process analytics for modeling, monitoring and analysis of processes in such complex business information systems. Business processes from large-scale companies are manifold and complex, resulting in the generation of vast amounts of business process data. Even though most such processes are executed using well-organized information systems, with corresponding business rules, yet flawlessness in their execution can never be guaranteed during the complexity and high volume of such business processes. Various internal and external influences can lead to uncertainty of process outcomes, as reflected in the process logs consisting of a collection of instances alongside their respective tasks and durations, from associated customer journeys and information management systems. Smart process analytics allows the users of these information systems to achieve their business goals in a much simpler way. Applications of different analytical techniques, such as process mining, empowers the users to get in-depth knowledge of the executing process. Applications of process mining create a basis for the deeper analysis of processes to rectify the possible flaws and facilitate timely predictions.
All accepted regular and poster papers will be published through IEEE-SWC21-SPA by IEEE CPS (IEEE-DL and EI indexed). At least one author of each accepted paper is required to register and present their work at the conference; otherwise, the paper will not be included in the proceedings. Best Paper Awards will be presented to high-quality papers. Selected papers will be recommended to special issues.