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Presentation in
TUDelft
范正洁
Fan Zhengjie
 Personal
Introduction
 MSc-thesis
 PhD
Plan
Work
 Personal
Introduction
 MSc-thesis
 PhD
Plan
Work
Personal Introduction
I come from Bengbu, Anhui, China
Education
B.E.(major) of Computer Science, Anhui
University, China, 2005
 B.A.(minor) of English, Anhui University,
China, 2005
 M.E. of Applied Computer Technology,
University of Science and Technology of
China, China, 2008

Research Interests
Artificial Intelligence and its application on
the web
 Semantic Web
 Semantic Web Service
 Multi-Agent System
 Ontology
 Data Mining and Machine Learning

Hobby
Classical music
 Singing
 Yoga
 Playing the accordion

 Personal
Introduction
 MSc-thesis
 PhD
Plan
Work
MSc-thesis Work
Two ranking methods in Discovery process
of Semantic Web Service.
 RASC
Algorithm
 RAUP Algorithm
Background
Two main directions of web improvement:
 Semantic Web: adding semantic on the
web
 Web Service: providing automatic services
online

Semantic Web Service: combining
technologies of both Semantic Web and
Web Service to fulfill automatic computation
Web Service lacks semantic support!
Syntax only!
Discovery
Discovery is a very important process of SWS,
which consists of two steps:
 Matching: comparing the function web user
wants with the one web services provide;
 Ranking: putting all matched web services
into an ordered list on certain criteria.
Ranking should be worked on.
Ranking criteria

Serving Capability

User Preference

Service Quality
RASC Algorithm
Core idea:
 “rewriting”: meeting as much as web user’s
output, asking as fewer as web user’s input
Comparison on output—1st dimension ranking
criteria
 Comparison on input—2nd dimension ranking
criteria

RASC
Algorithm:
Output comparison:
Input comparison:
Ranking:
Example
Output
relationship:
Input relationship:
Ordered list:
Discussion
Time complexity is O(n2),
Space complexity is O(n).
Comparing input and output seperately
 Adding input comparison as part of
ranking criteria, which reflects the
interation requirement of web user.

Experiment
Tools:
 Logic reasoner
RACER
 Coding language
Java
 Server with
processor AMD
4000+,memory 2G
Discussion:
 Ranking step
costs quite a few
executing time
RAUP Algorithm
Core ideas:
Drawing preference information by
interacting with web users
 Putting on relative weights on properties and
values
 Ranking on sum of weights

Algorithm
1. Selecting pairs of web services randomly and sending
them to web user to compare;
2. Classifying web services into two web service sets
according to users' answers;
3. Extracting user preference from two web service sets by
Apriori Algorithm;
4. Sending the drawn preference to the user to check;
5. Quantifying the checked preference by setting weights;
6. Computing each web service's sum of weights and
ranking them into an ordered list.
Example
web services:
Selected pairs:
User preference:
P1=Q11, P3=Q31
Classification: preferred web services set is {S2, S3, S1, S5, S5},
non-preferred web services set is {S1, S4, S3, S2, S4,}.
Preferred set:
Frequent
properties:
Non-preferred set:
∴no preference on properties
Frequent
values:
Preferred set:
Non-preferred set:
Case 1:
Case 2:
After user checking, Case 1 is the best choice.
Weights of properties:
Weights of values:
∵
set
∴
Sum of weights:
Result of ranking:
Discussion
Time complexity is O(r2),
Space complexity is O(r).
Drawing preference information by
interaction
 Weighing properties and values on their
contribution on discovery

Fulfilling individual oriented.
Experiment:
Tools:
 Coding language Java
 Server with processor
AMD 4000+, memory
2G
Discussion:
 Low executing time
 Drawing majority
preference
 Personal
Introduction
 MSc-thesis
 PhD
Plan
Work
Semantic Interoperability
Three kinds of data interoperability:
System interoperability
 Syntax and structure interoperability
 Semantic interoperability:
heterogeneity

Solution
 Ontology
 Process
Mapping
Mapping
Building a basic domain ontology
 Merging other ontologies into the basic
domain ontology
 Computing the relationship between two
processes based on the same ontology

Thank you!