1. Semantic Web services selection based on context information Hong Qing Yu Department of Computer Science 22th May 2007

2. Guideline Semantic Web services Context model Motivating example A modified LSP method for services selection Worked example Conclusion

3. Semantic Web services Software/component database Information application interface WSDL Semantics meta-model QoS Policies

4. Context Model [2]

5. Example for dynamic service selection [2]

6. LSP Method Logic scoring preference (LSP) method: is a quantitative method based on scoring techniques and a continuous preference logic [1]. [3]

7. Modified LSP Method 1) The type-based LSP evaluation methods (1) Exact match(2) Set overlap(3) Level match (4) Specific value

8. Modified LSP Method 2) Static global aggregation structure

9. Worked Example Desired preferences WeightMethodsCritical preferences WeightMethods Performance0.5(4)Protocol0.1(1) Devices0.2(2)Security0.2(1) Privacy0.05(3)Location0.1(1) Cost-0.05(4)Language0.1(2) Bank cards0.2(2) S Service1 =0.333 S Service2 =0S Service3 =0S Service4 =0.493 {Service 4, Service 1} The r = 3

10. Conclusion Semantic Web services Context model Motivating example A modified LSP method for services selection Worked example

11. 1.Covering the definition of the meanings of weights used in this paper from the perspective of user preferences, context mining and reasoning techniques since their outcomes will be the inputs for web service evaluation and selection. 2.Refining the rules for invoking the evaluation methods 3.Context aggregation problems 4.Additionally, implementation issues of the modified LSP method, as well as related mechanisms will be addressed. Future work will Future Work