Semantically Coordinated E-Market

27 January 2005 1

Semantically Coordinated E-Market

Semantic Web Term Project

Prepared by

Melike Şah

27 January 2005

27 January 2005 Semantically Coordinated E-Market – Melike Şah 2

Outline

Introduction Implementation

Technology base Ontology Representation Inference Engine Product Search

Demo Comparison Conclusion References


Introduction

Semantic Web Content with formal semantics; RDF/XML, RDFS,

OWL Machines understand content (intelligent agents) More automated functions (reasoning)

Resource Description Framework (RDF) XML-based language to describe resources Create metadata about document All resources described in RDF denoted via URI RDF model called a “triple”, (subject, predicate, object) Statement is combination of triples


Introduction (Cont.)

RDF Schema (RDFS) Defined relationships among classes/resources

Web Ontology Language (OWL) Complex applications may require more capabilities Cardinalities, property restrictions Class operations (union, intersection,…)

E-Market uses OWL to represent product info. Inference engine to reason on data Purpose is effective product search with

OWL Reasoning engine

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Implementation

Technology base

Ontology

Product Search


Technology Base

Protégé – Ontology RepresentationJava-based graphical toolOWL plugin - Ontology editingOWL classes, properties, restrictionsRDF/XML syntax

Algernon – Inference Engine Implemented in Java, portable with ProtégéQuerying with ASK statement Inserting facts with TELL statement


Ontology Representation with Protégé

Figure 1: UML diagram of E-Market Ontology


Ontology (Cont.)

Ontology of E-Market is created with OWL with RDF/XML syntax

Protégé is used for producing classes properties relations individuals


Ontology (Cont.)

Classes are type of owl:Class and Products is broken into specialized Classes

<owl:Class rdf:ID="Fishes"> <rdfs:subClassOf> <owl:Class rdf:about="#Products"/> </rdfs:subClassOf></owl:Class>


Ontology (Cont.)

Properties product_name, price, day, month and year are owl:DatatypeProperty

<owl:DatatypeProperty rdf:about="#price">

<rdfs:domain rdf:resource="#Products"/>

<rdfs:range rdf:resource="http://www.w3.org/2001/XMLSchema#float"/>

</owl:DatatypeProperty>


Ontology (Cont.)

Relations has_relation_vegetables and has_relation_leguminous are owl:ObjectProperty

<owl:ObjectProperty rdf:ID="has_relation_vegetables">

<rdfs:range rdf:resource="#Vegetables"/>

<rdfs:domain rdf:resource="#Leguminosae"/>

</owl:ObjectProperty>


Ontology (Cont.)

Total of 63 individuals are generated<Fresh rdf:ID="melike_Individual_44">

<product_name rdf:datatype="http://www.w3.org/2001/XMLSchema#string">

anchovy500gr</product_name>

<price rdf:datatype="http://www.w3.org/2001/XMLSchema#float">5.0</price>

<month rdf:datatype="http://www.w3.org/2001/XMLSchema#int">1</month>

<year rdf:datatype="http://www.w3.org/2001/XMLSchema#int">2005</year>

<day rdf:datatype="http://www.w3.org/2001/XMLSchema#int">18</day>

</Fresh>


Product Search

Algernon inference engine usedPurpose: effective product querying with

ontologies and inference engineSame search is tested on database-end

E-Market with SQL


Product Search with Algernon

“Search all Pepsi Products” with Algernon

Figure 2: Algernon Query searches all Pepsi products


Product Search with SQL

Search all Pepsi products with SQLSELECT [product_name], [price]

FROM products, Colas, Pepsi

WHERE [Products].[P_ID]=[Colas].[C_ID] And

[Colas].[C_ID]=[Pepsi].[pepsi_ID];

Figure 3: SQL Query searches all Pepsi products


Demo

Search examples


Comparison

Data have semantics; ontologyReason about ontologyNo need to know all class names and

details of informationMore effective search

a query could return comparative pricesa query could offer products if the searched

product is not found


Conclusion

Formal semanticsMachine usable dataIncreased usability of dataReasoning on ontology to further

enhanced the search


References

[1] Tim Berners-Lee, “The Semantic Web Roadmap”, W3C Draft Document, Sep. 1998, http://www.w3.org/DesignIssues/Semantic.html.

[2] Tim Berners-Lee, “The Semantic Web", Oct. 30, 2000, Newsweek interview, http://www.keepmedia.com/pubs/Newsweek/2000/10/30/317242.

[3] Electronic Markets - The International Journal of Electronic Commerce and Business Media, web site http://www.electronicmarkets.org/.

[4] OWL Web Ontology, site of W3C, http://www.w3.org/2004/OWL/. [5] OWL Web Ontology Language Guide: W3C Recommendation 10 Feb

2004. Smith, Welty, McGuinness, eds, http://www.w3.org/TR/owl-guide/.[6] OWL Web Ontology Language Overview: W3C Recommendation 10 Feb

2004. Deborah L. McGuinness and Frank van Harmelen eds, http://www.w3.org/TR/owl-features/.

[7] Reasoning Engine[8] Protégé overview, web site http://protege.stanford.edu.[9] N. F. Noy, M. Sintek, S. Decker, M. Crubezy, R. W. Fergerson, & M. A.

Musen. “Creating Semantic Web Contents with Protege-2000”, IEEE Intelligent Systems 16(2):60-71, 2001.


References (Cont.)

[10] J. Gennari, M. A. Musen, R. W. Fergerson, W. E. Grosso, M. Crubézy, H. Eriksson, N. F. Noy, S. W. Tu, “The Evolution of Protégé: An Environment for Knowledge-Based Systems Development”, 2002, Technical Report.

[11] Stanford University, http://smi.stanford.edu/.[12] Algernon Overview, web site

http://algernon-j.sourceforge.net/doc/overview.html. [13] Algernon Rule Base Programming, http://algernon-j.sourceforge.net/.[14] Algernon in Java commands,

http://algernon-j.sourceforge.net/doc/commands/[15] Algernon in Java Documentation, http://algernon-j.sourceforge.net/doc/[16] Using ASK and TELL to interact with Algernon V3,

http://www.cs.utexas.edu/users/qr/algy/ask-tell.html[17] Algernon Tutorial, forward-chaining rules, TELL statement,

http://algernon-j.sourceforge.net/tutorial/3c.html[18] University of Texas at Austin Computer Sciences Department,

http://www.cs.utexas.edu/[19] Algernon Abstract Machine,

http://www.cs.utexas.edu/ftp/pub/AI-Lab/tech-reports/UT-AI-TR-00-284.ps.Z

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Semantically Coordinated E-Market