Identifying and Eliminating Inconsistencies in Mappings across Hierarchical Ontologies

Many applications require the establishment of mappings between ontologies. Such mappings are established by domain experts or automated tools. Errors in mappings can introduce inconsistencies in the resulting combined ontology. We consider the problem of identifying the largest consistent subset of mappings in hierarchical ontologies. We consider mappings that assert that a concept in one ontology is a subconcept, superconcept, or equivalent concept of a concept in another ontology and show that even in this simple setting, the task of identifying the largest consistent subset is NP-hard. We explore several polynomial time algorithms for finding suboptimal solutions including a heuristic algorithm to this problem. We experimentally compare the algorithms using several synthetic as well as real-world ontologies and mappings.
Our past work has investigated the use of the Cognitive Model Software Development Kit (SDK) for creating the cognitive models that underlie model-tracing Cognitive Tutors. Though successful at increasing the number of people who could author such a cognitive model, for certain kinds of situations the Cognitive Model SDK proved cumbersome. The present work discusses a new authoring system, xPST, that allows an example-based tutor to be built on top of existing software. xPST-based tutors have been built for two real-world systems that had existing interfaces.