language: en

Explaining Anomalies as a Basis for Knowledge Base Refinement

Neli P. Zlatareva
Department of Computer Science Central Connecticut State University
New Britain, CT 06050

Abstract Explanations play a key role in operationalization-based anomaly detection techniques. In this paper we show that their role is not limited to anomaly detection; they can also be used for guiding automated knowledge base refinement. We introduce a refinement procedure which takes: (i) a small number of refinement rules (rather than test cases), and (ii) explanations constructed in an attempt to reveal the cause (or causes) for inconsistencies detected during the verification process, and returns rule revisions aiming to recover the consistency of the KB-theory. Inconsistencies caused by more than one anomaly are handled at the same time, which improves the efficiency of the refinement process.

1 Introduction