Semantic Filtering for DDL-Based Service Composition

Authors:
Wenjia Niu;Zhongzhi Shi;Peng Cao;Hui Peng;Liang Chang
Affiliations:
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China 100190 and Graduate School of the Chinese Academy of Sciences, ...;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China 100190;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China 100190 and Graduate School of the Chinese Academy of Sciences, ...;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China 100190 and Graduate School of the Chinese Academy of Sciences, ...;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China 100190 and Graduate School of the Chinese Academy of Sciences, ...
Venue:
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2008

Citing 4
Cited 1

Data integration using similarity joins and a word-based information representation language

ACM Transactions on Information Systems (TOIS)
ConChat: A Context-Aware Chat Program

IEEE Pervasive Computing
An operational definition of context

CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
A dynamic description logic for representation and reasoning about actions

KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management

Multi-granularity context model for dynamic Web service composition

Journal of Network and Computer Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Dynamic description logic (DDL) provides a good logic-level solution among the few emerging service composition solutions through reasoning in AI area. To make DDL reasoning infrastructure practical, there is still unaddressed needs of increasing reasoning efficiency. We proposed a semantic filtering approach aiming to increase reasoning efficiency through decreasing reasoning space. The filtering approach was decomposed into two consecutive steps: context-based semantic retrieval with iRDQL --(an imprecise query model, and processing of retrieval results under the control of workflow before forming final filtering results. Experimental results show that the method is well suitable for the volatile context-aware environment and yields good performance over DDL-based service composition.