Our Ph.D. student, Michael Arias, offered the presentation “Data Science and Process Mining” in the XXIV Congreso Nacional de Estudiantes de Ingenería de Sistemas y Computación (CONEISC 2016) in Pucallpa, Peru. During his visit Michael talk about the ideas behind the link between data science and process mining, available process mining tools, and also share some details about his research in the resource allocation topic.
The Process Mining UC research group congratulates Michael Arias, Jorge Munoz-Gama and Marcos Sepúlveda, for their accepted paper in the 1st workshop on Resource Management in Business Processes 2016 (ReMa’16), organized in conjunction with 14th International Conference on Business Process Management (BPM 2016), which will be held in the city of Rio de Janeiro between September 18th and 22nd of 2016.
The name of the accepted article is “A Multi-criteria Approach for Team Recommendation”.
General framework for Team Resource Recommendation
This work presents a novel approach that recommends the most suitable teams to execute a request defined at run-time. The approach considers four elements: (i) a resource request characterization, (ii) historical information on the process execution and expertise information, (iii) different metrics which calculate the suitability of the work teams taking into account both individual performance as well as collective performance of the resources, and (iv) a recommender system based on the Best Position Algorithm (BPA2) to obtain a ranking for the recommended work teams.