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Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

14 pagesPublished: December 10, 2019

Abstract

This paper deals with querying ontology-based knowledge bases equipped with non-monotonic rules through a case study within the framework of Cultural Heritage. It focuses on 3D underwater surveys on the Xlendi wreck which is represented by an OWL2 knowledge base with a large dataset. The paper aims at improving the interactions between the archaeologists and the knowledge base providing new queries that involve non-monotonic rules in order to perform qualitative spatial reasoning. To this end, the knowledge base initially represented in OWL2-QL is translated into an equivalent Answer Set Programming (ASP) program and is enriched with a set of non-monotonic ASP rules suitable to express default and exceptions. An ASP query answering approach is proposed and implemented. Furthermore due to the increased expressiveness of non-monotonic rules it provides spatial reasoning and spatial relations between artifacts query answering which is not possible with query answering languages such as SPARQL and SQWRL.

Keyphrases: answer set programming, cultural heritage, knowledge base, ontology, reasoning

In: Diego Calvanese and Luca Iocchi (editors). GCAI 2019. Proceedings of the 5th Global Conference on Artificial Intelligence, vol 65, pages 94-107.

BibTeX entry
@inproceedings{GCAI2019:Query_Answering_With_Non,
  author    = {Mohamed Ben Ellefi and Pierre Drap and Laurent Garcia and Fabien Garreau and Claire Lefèvre and Odile Papini and Igor Stéphan and Eric Würbel},
  title     = {Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning},
  booktitle = {GCAI 2019. Proceedings of the 5th Global Conference on Artificial Intelligence},
  editor    = {Diego Calvanese and Luca Iocchi},
  series    = {EPiC Series in Computing},
  volume    = {65},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/gl5c},
  doi       = {10.29007/6ph5},
  pages     = {94-107},
  year      = {2019}}
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