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Journal of Zhejiang University SCIENCE C 2012 Vol.13 No.4 P.250-252

http://doi.org/10.1631/jzus.C1101004


Local closed world reasoning: a personal view on current status and trends


Author(s):  Jeff Z. Pan, Yuan Ren

Affiliation(s):  Department of Computing Science, University of Aberdeen, Aberdeen AB24 3UE, UK

Corresponding email(s):   Jeff.z.pan@abdn.ac.uk, y.ren@abdn.ac.uk

Key Words:  No Keyword


Jeff Z. Pan, Yuan Ren. Local closed world reasoning: a personal view on current status and trends[J]. Journal of Zhejiang University Science C, 2012, 13(4): 250-252.

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author="Jeff Z. Pan, Yuan Ren",
journal="Journal of Zhejiang University Science C",
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doi="10.1631/jzus.C1101004"
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%T Local closed world reasoning: a personal view on current status and trends
%A Jeff Z. Pan
%A Yuan Ren
%J Journal of Zhejiang University SCIENCE C
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1101004

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T1 - Local closed world reasoning: a personal view on current status and trends
A1 - Jeff Z. Pan
A1 - Yuan Ren
J0 - Journal of Zhejiang University Science C
VL - 13
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SP - 250
EP - 252
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1101004


Abstract: 
LCWR with ontologies have opened a new horizon for ontology applications: 1. Combining ontologies with relational databases. The inter-operability between relation databases and DL-based ontologies is one of the most interesting topics in ontology applications, especially for industrial audience. LCWR bridges one of the biggest gaps between legacy relational database systems and ontology based systems. With LCWR supported by reasoners, users can specify the closure of certain classes/properties so that the semantics of their database remains the same when they are combined with ontologies. 2. Ontology-based recommendation systems. Due to the semantics of the OWA, anything derived by legacy reasoning technologies must be absolutely true facts. Possible (i.e., not definite) solutions cannot be derived by reasoning because they are not logical implications of the ontology. With LCWR, a user can close the class of definitely wrong answers, and then its complement becomes the set of possible answers. Such a pattern can be widely applied in recommendation services, such as system configuration and repairing, diagnosis and matchmaking, etc. 3. Non-monotonic ontology reasoning. Classical ontology reasoning is monotonic in a sense that adding new knowledge into an ontology will not retract existing conclusions. However, with LCWR, non-monotonic reasoning is realized. It will be a very interesting research topic to investigate the relationship between LCWR and other non-monotonic reasoning services, and to develop theories that can provide a unified explanation for these services. To sum up, a range of new applications can be incubated by the utilization of LCWR technologies, and the research work on these topics will have significant industrial and academic impacts. To facilitate the wide acceptance of LCWR, ontology system developers and researchers will have to address different technical issues. For developers, it is crucial to know the pros and cons and tool support of each different LCWR solution and identify their own requirements, so that they can find out which solution is most suitable and available for them. For researchers it will be important to investigate the connections between different LCWR solutions and discover the possibility of using them complementarily to overcome the limitations of each other. Furthermore, new technologies should be developed with the collaboration of both communities to improve the user-friendliness of LCWR. Particularly, because LCWR is non-monotonic, it will be very important to help users understand how the ontology and reasoning results will be changed if they decide to close or open certain predicates. These are all future directions we will be looking into.

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Reference

[1]Motik, B., Rosati, R., 2010. Reconciling description logics and rules. J. ACM, 57(5):1-63.

[2]Motik, B., Horrocks, I., Sattler, U., 2009. Bridging the gap between OWL and relational databases. J. Web Semant., 7(2):74-89.

[3]Ren, Y., Pan, J.Z., Zhao, Y., 2010. Closed world reasoning for OWL2 with NBox. J. Tsinghua Sci. Technol., 15(6):692-701.

[4]Sengupta, K., Krisnadhi, A.A., Hitzler, P., 2011. Local closed world reasoning: grounded circumscription for OWL. LNCS, 7031:617-632.

[5]Seylan, I., Franconi, E., de Bruijn, J., 2009. Effective Query Rewriting with Ontologies over DBoxes. Proc. 21st Int. Joint Conf. on Artificial Intelligence, p.923-929.

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