PANDA: Human-in-the-Loop Anomaly Detection and Explanation

• Published in: Information Processing and Management of Uncertainty in Knowledge-Based Systems Vol. 1602; pp. 720 - 732
• Main Authors: Smits, Grégory, Lesot, Marie-Jeanne, Yepmo Tchaghe, Véronne, Pivert, Olivier
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2022; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Fuzzy vocabulary; Human-in-the-loop; Linguistic description; Outlier detection; Outlier explanation; XAI
• ISBN: 9783031089732; 3031089731
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-031-08974-9_57

The paper addresses the tasks of anomaly detection and explanation simultaneously, in the human-in-the-loop paradigm integrating the end-user expertise: it first proposes to exploit two complementary data representations to identify anomalies, namely the description induced by the raw features and the description induced by a user-defined vocabulary. These representations respectively lead to identify so-called data-driven and knowledge-driven anomalies. The paper then proposes to confront these two sets of instances so as to improve the detection step and to dispose of tools towards anomaly explanations. It distinguishes and discusses three cases, underlining how the two description spaces can benefit from one another, in terms of accuracy and interpretability.