Belief base revision for datalog+/- ontologies

Songxin Wang, Jeff Z. Pan*, Yuting Zhao, Wei Li, Songqiao Han, Dongmei Han

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Datalog+/- is a family of emerging ontology languages that can be used for representing and reasoning over lightweight ontologies in Semantic Web. In this paper, we propose an approach to performing belief base revision for Datalog+/- ontologies. We define a kernel based belief revision operator for Datalog+/- and study its properties using extended postulates, as well as an algorithm to revise Datalog+/- ontologies. Finally, we give the complexity results by showing that query answering for a revised linear Datalog+/- ontology is tractable.

Original languageEnglish
Title of host publicationThird Joint International Conference (JIST 2013)
Subtitle of host publicationSemantic Technology
EditorsWooju Kim, Ying Ding, Hong-Gee Kim
PublisherSpringer-Verlag
Pages175-186
Number of pages12
ISBN (Electronic)9783319068268
ISBN (Print)9783319068251
DOIs
Publication statusPublished - 2014
Event3rd Joint International Semantic Technology Conference, JIST 2013 - Seoul, Korea, Republic of
Duration: 28 Nov 201330 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8388 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference3rd Joint International Semantic Technology Conference, JIST 2013
CountryKorea, Republic of
CitySeoul
Period28/11/1330/11/13

Fingerprint

Datalog
Ontology
Belief Revision
Postulate
Reasoning
Semantics
Beliefs
Query
kernel
Operator

Keywords

  • Datalog+/-
  • Ontology
  • Belief revision
  • Kernel

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wang, S., Pan, J. Z., Zhao, Y., Li, W., Han, S., & Han, D. (2014). Belief base revision for datalog+/- ontologies. In W. Kim, Y. Ding, & H-G. Kim (Eds.), Third Joint International Conference (JIST 2013): Semantic Technology (pp. 175-186). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8388 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-06826-8_14

Belief base revision for datalog+/- ontologies. / Wang, Songxin; Pan, Jeff Z.; Zhao, Yuting; Li, Wei; Han, Songqiao; Han, Dongmei.

Third Joint International Conference (JIST 2013): Semantic Technology. ed. / Wooju Kim; Ying Ding; Hong-Gee Kim. Springer-Verlag, 2014. p. 175-186 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8388 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, S, Pan, JZ, Zhao, Y, Li, W, Han, S & Han, D 2014, Belief base revision for datalog+/- ontologies. in W Kim, Y Ding & H-G Kim (eds), Third Joint International Conference (JIST 2013): Semantic Technology. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8388 LNCS, Springer-Verlag, pp. 175-186, 3rd Joint International Semantic Technology Conference, JIST 2013, Seoul, Korea, Republic of, 28/11/13. https://doi.org/10.1007/978-3-319-06826-8_14
Wang S, Pan JZ, Zhao Y, Li W, Han S, Han D. Belief base revision for datalog+/- ontologies. In Kim W, Ding Y, Kim H-G, editors, Third Joint International Conference (JIST 2013): Semantic Technology. Springer-Verlag. 2014. p. 175-186. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-06826-8_14
Wang, Songxin ; Pan, Jeff Z. ; Zhao, Yuting ; Li, Wei ; Han, Songqiao ; Han, Dongmei. / Belief base revision for datalog+/- ontologies. Third Joint International Conference (JIST 2013): Semantic Technology. editor / Wooju Kim ; Ying Ding ; Hong-Gee Kim. Springer-Verlag, 2014. pp. 175-186 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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