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EASTERN MEDITERRANEAN UNIVERSITY

COMPUTER ENGINEERING DEPARTMENT

Presented ByDuygu CELIK

Supervised ByAtilla ELCI

Intelligent Semantic Web Service Finder (ISWSF) System

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I. INTODUCTION

The shortage of semantic parts, increasing number of web services in the web, and syntactic-based search operation are the main problems of current Web service technologies.

These problems make discovering of appropriate web services challenging.

This study provides an implementation of the intelligent semantic web service finder (ISWSF) system [5] that can be used to find related Semantic Web Services based on an client’s request through a semantic search agent (SSA)

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Solution (cont)

The system understands ontologies, concepts of

Semantic Web Services and connects to each of

these services.

Has ability to extracts necessary profile

information of services for choosing best

Semantic Web Services (SWS) based on the

client request.

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II. System parts (ISWSF)

Client Interface Semantic Web Services (SWS) and OWL-S

Files Semantic Search Agent UDDI Registry (Universal Description, Discovery

and Integration. ) Ontology Database (OWL Files)

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VI. IMPLEMENTATION

Figure 5. Used modules for implementation of ISWSF.

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JAVA Net Beans 4.0 Java Server Pages (JSP) Java Classes

Jena 2.0 Ontology API OWL-S API Protégé 3.1 (Ontology

creator/edit tool) Created OWL Files Created OWL-S Files

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2.1 What is Semantic Web Service and OWL-S

SWS provides machine-readable descriptions of web services, which enable automated discovery, negotiation with, composition, execution, and monitoring of web services.OWL-S and Relation of SWSOntology languages provide a way for describing their formal specification and have the ability to define properties of the Web Services (OWL-S)

Through property description capabilities of ontology languages, descriptions of services can be defined more accurately and services can be related to other services or resources more easily.

This study attempts to motivate OWL-S for discovering appropriate Web Services.

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2.2 What is UDDI?

UDDI is a standard for discovery of Web Services that stands for Universal Description, Discovery and Integration.

The UDDI registry can be classified into two categories which are UDDI-Web Services and UDDI-Business Registry.

The Web Service developers publish their web services to the UDDI registry.

Once published, the UDDI registry holds information of web service description and address.

The UDDI allows clients to search this registry, find the planned service and retrieve its details.

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III. System Tasks

System has two tasks;

1. Semantic Enhancement of clients input termsperforms enhancement of the terms entered by the client with its synonym(s) or is_a relations.

2. Matching StepThe system checks if there is a match between clients’ request info and the profile information (ontologies) of SWSs.

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The proposed system combines further aspects of two research topics: Smart Web Query Engine[1] Matchmaking Algorithm of OWL-S/UDDI

Matchmaker[2,3,4 and 5] To facilitate the finding of semantic web services

for a client.

IV. Survey

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V. SYSTEM ARCHITECTURE

Figure 1. The System Architecture of ISWSF.

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A Client

Ontology Database(created in OWL)

For Domain

UDDI Registry(Stores Web

Services’Information &

Addresses)

Semantic Web Services

(retrieve from UDDI)

SSA

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A. Semantic Enhancement of Input Terms

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Figure 2. Semantic Enhancement of Input

Term(s).

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B. Matching Step

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Figure 3. Matching Step.

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6.2 Created OWL Files in Protégé 3.1 The Protégé 3.1 used for creating ontologies and

its classes, individuals and properties. The system is able to use those ontologies for

retrieve relations between terms. (Vehicle Ont.)

Figure 6. Created the Vehicle Ontology in Protégé 3.1 and system used it for Retrieve relations between Terms.

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oseparate rules as exact, plug in, subsumes and fail

o outR is one output of the request

o outA is output of the advertisement

What are rules for matching operation?

Figure 4. Rules for Degree of Match Assignment, [1]

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degreeOfMatchStep(R,A):

if (R=A) or (hasSynR=A) or (R=hasSynA) then return sc=3

if (R A) or (hasSynR A) or (R hasSynA) or (hasIs_aR A) or (R hasIs_aA) then return sc=2

if (R A) or (hasSynR A) or (R hasS

ynA) or (hasIs_aR A) or (R hasIs_aA) then return sc=1

if (R A) or (hasSynR A) or (R hasSynA) or (hasIs_aR A) or (R hasIs_aA) then return sc=0

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The WordNet [12], which was developed by the Cognitive Science Laboratory at Princeton University under the

direction of Professor George A. Miller.

1. WordNet is an online lexical reference system.2. English nouns, verbs, adjectives and adverbs are arranged into

synonym sets, each synonym set is representing one primary lexical concept. Various relations connect the synonym sets.

3. A set of words that can be observed as exacting synonyms is called a Synset. For a queried word, finding the different synsets that contain the word, and finding related synsets.

Figure 7. Search the term “Car” in WordNet

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6.2 How create OWL-S (Semantic Web Services) files?

A new semantic technology OWL-S, can be used to develop SWSs descriptions. In this project we use OWL-S and OWL-S Editor and this OWL-S Editor aims to create an easy-to-use editor for creating OWL-S Ontology files for services.

The editor is a Tab Widget plug-in for Protégé The ISWSF system used the inputs and outputs of the Profile classes of the SWS and then compare them with client inputs and outputs.

Figure 8. A Part of the Online Car Parts Selling Service in OWL-S Editor (In Profile Information)

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VII.CASE STUDY

A client looking for a Online Car Parts Selling Service Client enters the term “CAR” in to ISWSF The system tries to find which ontologies include the term Client selects the related ontology name The system will operate on only that Ontology anymore Client enters I/O parameters The system will begin to perform Matching Step Compare between each client terms with each profile

information in OWL-S files for each SWSs

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Vehicle Example

A Vehicle example: A client is looking for Online Car Parts Selling Service

Search Key:Car

INPUTS:CarParts

OUTPUTS:Price

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Vehicle Example (Cont.)

Figure 9. The client enters number of key words for search operation

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Vehicle Example (Cont.)

Figure 10. The client enters “Car” term.

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Vehicle Example (Cont.)

Figure 11. The system found the related ontologies.

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Vehicle Example (Cont.)

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Figure 12. The system shows the results of the "Car" term’s synonym and is_a terms.

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Figure 13. The system is showing the results of the “Car" term’s synonym terms.

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Vehicle Example (Cont.)

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Figure 14. Client enters I/O informations.

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Vehicle Example (Cont.)

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Vehicle Example (Cont.)

Figure 15. Returned results of matchmaking step.

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Vehicle Example (Cont.)

Figure 16. SSA returned best SWS for client after matching process.

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•The system performs two main functions, namely, enhancing client request term with synonym or relational terms and matchmaking step between the SWS I/O and client I/O. •The system specifies relationships between those input/output parameters as EXACT, PLUGIN, SUBSUME and FAIL. According to those relationships the system serves appropriate web services to the client based on the client request.

CONCLUSION

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REFERENCES

[1] http://www.w3.org/TR/soap/ [2] http://www.w3.org/TR/wsdl.html [3] http://www.uddi.org/[4] http://owlseditor.semwebcentral.org/[5] D. Çelik and A. Elçi: A Semantic search agent

approach: Finding appropriate semantic Web services based on user request term(s), Enabling Technologies for the New Knowledge Society, ITI 3rd International Conference on Information & Communication Technology (ICICT 2005), 5-6 December 2005, Cairo, Egypt. Proc.: IEEE publ. to appear, http://www.icict.gov.eg/ICICT2005/

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[6] Roger H.L. Chiang, Cecil Eng Huang Chua and Veda C. Storey, A smart web query method for semantic retrieval of web data, Data & Knowledge Engineering, Volume 38, Issue 1,July2001,Pages63-84, http://www.sciencedirect.com/sciencehttp://www.kns.dlr.de/Projects/spreading/spreading190198.html.

[7] K. Sycara, M. Paolucci, A. Ankolekar and N. Srinivasan, "Automated Discovery, Interaction and Composition of Semantic Web services," in Journal of Web Semantics, Volume 1, Issue 1, September 2003, pp. 27-46.

[8] N. Srinivasan, M. Paolucci and K. Sycara, "Adding OWL-S to UDDI, implementation and throughput."First International Workshop on Semantic Web Services and Web Process Composition **(SWSWPC 2004) 6-9, 2004, San Diego, California, USA.

REFERENCES (Cont.)

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[9] Massimo Paolucci, Takahiro Kawamura, Terry R. Payne, Katia Sycara; "Importing the Semantic Web in UDDI," in Proceedings of Web Services, E-business and Semantic Web Workshop

[10] T. Kawamura, J. A. De Blasio, T. Hasegawa, M. Paolucci, and K. Sycara, "A Preliminary Report of a Public Experiment of a Semantic Service Matchmaker combined with a UDDI Business Registry," in 1st International Conference on Service Oriented Computing (ICSOC 2003), Trento, Italy, December 2003.

REFERENCES (Cont.)

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Thank you for attention!