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Project - AI explainability Improve performance of explainability algorithms. Available Apply By27/05/22
Project - Multi-perspective Process Concept Drift Detection The project aims to explore multi-perspective concept drift detection for processes using event logs. Further, it should provide explanation/root cause for detected drifts. In progress
Project - Machine Learning in Data Quality Space – Anomaly Detection Project Description: In the current data age, quality of the data becomes center place for any enterprise data strategy. The issue of poor data quality is hindering organizations from performing to their full potential. Gartner’s data quality market survey estimated that the financial impact caused by data quality issues is in millions. Traditionally organizations have used a combination of manual and automatic methods to tackle this issue in siloed approaches. In progress
Project - Generating Predictions and Explanations for Business Processes Using Graph Neural Networks The objective of this project is to explore the use for Graph Neural Networks based predictions that model relevant attributes of the business process and provide explainable predictions. The task of prediction process outcomes and next activity will be explored in this work. A method to evaluate the explanations will also be developed. In progress
Project - Dashboard for Product Usage Analytics Analysis of user clicks on the web portal In progress