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| a decomposition-based approach to owl dl ontology diagnosis | |
| Du Jianfeng; Qi Guilin; Pan Jeff Z.; Shen Yi-Dong | |
| 2011 | |
| Conference Name | 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011 |
| Source | Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI |
| Pages | 659-664 |
| Conference Date | November 7 |
| Conference Place | Boca Raton, FL, United states |
| Indexed Type | EI |
| ISSN | 1082-3409 |
| ISBN | 9780769545967 |
| Department | (1) Guangdong University of Foreign Studies Guangzhou 510006 China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China; (3) School of Computer Science and Engineering Southeast University NanJing 211189 China; (4) Department of Computing Science University of Aberdeen Aberdeen AB243UE United Kingdom |
| English Abstract | Computing all diagnoses of an inconsistent ontology is important in ontology-based applications. However, the number of diagnoses can be very large. It is impractical to enumerate all diagnoses before identifying the target one to render the ontology consistent. Hence, we propose to represent all diagnoses by multiple sets of partial diagnoses, where the total number of partial diagnoses can be small and the target diagnosis can be directly retrieved from these partial diagnoses. We also propose methods for computing the new representation of all diagnoses in an OWL DL ontology. Experimental results show that computing the new representation of all diagnoses is much easier than directly computing all diagnoses. © 2011 IEEE.; Computing all diagnoses of an inconsistent ontology is important in ontology-based applications. However, the number of diagnoses can be very large. It is impractical to enumerate all diagnoses before identifying the target one to render the ontology consistent. Hence, we propose to represent all diagnoses by multiple sets of partial diagnoses, where the total number of partial diagnoses can be small and the target diagnosis can be directly retrieved from these partial diagnoses. We also propose methods for computing the new representation of all diagnoses in an OWL DL ontology. Experimental results show that computing the new representation of all diagnoses is much easier than directly computing all diagnoses. © 2011 IEEE. |
| Keyword | Artificial Intelligence Data Description Decomposition |
| Sponsorship | IEEE; IEEE Computer Society; IEEE Computer Society Technical Committee on Multimedia Computing; Biological and Artificial Intelligence Society (BAIS); Florida Atlantic University (FAU) |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16256 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Du Jianfeng,Qi Guilin,Pan Jeff Z.,et al. a decomposition-based approach to owl dl ontology diagnosis[C],2011:659-664. |
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