Uncertain Case Identifier

Uncertain case identifiers pose a significant challenge in various data analysis domains, hindering the effective processing and interpretation of information from diverse sources like user interaction logs and process data. Current research focuses on developing methods to resolve this uncertainty, employing techniques such as neural networks, sliding window approaches with distance metrics, and contrastive learning, often incorporating semi-supervised or positive-unlabeled learning strategies. These advancements are crucial for improving process mining, enhancing the accuracy of predictive models in fields like child welfare, and enabling more robust analysis of complex datasets across diverse applications.