Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4945264 | International Journal of Approximate Reasoning | 2017 | 22 Pages |
Abstract
This paper investigates an extension of lightweight ontologies, encoded here in DL-Lite languages, to the product-based possibility theory framework. We first introduce the language (and its associated semantics) used for representing uncertainty in lightweight ontologies. We show that, contrarily to a min-based possibilistic DL-Lite, query answering in a product-based possibility theory is a hard task. We provide equivalent transformations between the problem of computing an inconsistency degree (the key notion in reasoning from a possibilistic DL-Lite knowledge base) and the weighted maximum 2-Horn SAT problem. The last part of the paper provides an encoding of the problem of computing inconsistency degree in product-based possibility DL-Lite as a weighted set cover problem and the use of a greedy algorithm to compute an approximate value of the inconsistency degree. This encoding allows us to provide an approximate algorithm for answering instance checking queries in product-based possibilistic DL-Lite. Experimental studies show the quality of the approximate algorithms for both inconsistency degree computation and instance checking queries.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Khaoula Boutouhami, Salem Benferhat, Faiza Khellaf, Farid Nouioua,