Transcript e-Business - University of Leicester

Semantic Web services selection
based on context information
Hong Qing Yu
Department of Computer Science
22th May 2007
Guideline
•
•
•
•
Semantic Web services
Context model
Motivating example
A modified LSP method for services
selection
• Worked example
• Conclusion
Semantic Web services
QoS
Semantics meta-model
Policies
WSDL
interface
Information
application
database
Software/component
Context Model
[2]
Example for dynamic service
selection
[2]
LSP Method
Logic scoring preference (LSP) method: is a quantitative method based on
scoring techniques and a continuous preference logic [1].


e0 = W1e1 + ...+ Wk ek ,W1 + ...+ Wk = 1
[3]

e0 = W1e1r + ...+ Wk ekr

1/ r
,W1 + ...+ Wk = 1
d 1
e1  ...  ek
0.5  d  1
e1...ek
d  0.5
(e1  ...  ek ) / k
0  d  0.5
e1...ek
d 0
e1  ...  ek
Modified LSP Method
1) The type-based LSP evaluation methods
(1) Exact match
(2) Set overlap
(3) Level match
(4) Specific value
Modified LSP Method
2) Static global aggregation structure
EPCi
CWB1
.
.
.
.
.
.
CWAi
CWBi
with CW A1 + ... + CWAi = 0.5
DWA1 + ... + DW Aj = 1
and DWB0 = 0.5
CWB1 = CWA1 ... CWBi = CWAi
where DAC is D-+ .. A .. GEO
(DWA1)/2
D
EP
CWA1
j
.
.
.
(DWAj)/2
DAC
DWB
0
CA
GP
Worked Example
Desired
preferences
Weight
Methods
Critical
preferences
Weight
Methods
Performance
0.5
(4)
Protocol
0.1
(1)
Devices
0.2
(2)
Security
0.2
(1)
Privacy
0.05
(3)
Location
0.1
(1)
Cost
-0.05
(4)
Language
0.1
(2)
Bank cards
0.2
(2)
1
  (0.5  4  0.2  3  0.05  2  0.05)  0.6875
4
SService1=0.333
SService2=0
{Service 4, Service 1}
SService3=0
The r = 3
SService4=0.493
Conclusion
•
•
•
•
Semantic Web services
Context model
Motivating example
A modified LSP method for services
selection
• Worked example
Future Work
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.