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Cyprus Map Through Ontologies CMPE 583 - Web Semantics Project Prepared by Gizem OLGU Ali TÜZEL.

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Cyprus Map Through Ontologies CMPE 583 - Web Semantics Project Prepared by Gizem OLGU Ali TÜZEL
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Page 1: Cyprus Map Through Ontologies CMPE 583 - Web Semantics Project Prepared by Gizem OLGU Ali TÜZEL.

Cyprus MapThrough Ontologies

CMPE 583 - Web Semantics Project

Prepared byGizem OLGU

Ali TÜZEL

Page 2: Cyprus Map Through Ontologies CMPE 583 - Web Semantics Project Prepared by Gizem OLGU Ali TÜZEL.

Cyprus Map Through Ontologies 2Gizem OLGU and Ali TUZEL

Outline

Introduction Cyprus Map Ontologies

CyprusMapOnto_vGizem CyprusMapOnto_vAli

Ontology Combining Prompt Approach Similarity Approach

Demo Protege Demo MATLAB Demo

Conlusions & Future Works

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Introduction

Semantic Web Is an extension of the current web, in which information on the

web can processed by machines, in other words data becomes in machine-readable form on the web.

Ontology Is content theories about sort of object, properties of the object

and relation between objects that are possible in a specified domain of knowledge.

Ontology has identified with computer as a machine-readable vocabulary.

The OWL (Web Ontology Language)

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Introduction - Case

The Purpose Combining the different ontologies using similarity approach.

The Subject Proposed case study is based on Cyprus Map.

Two different Cyprus Map ontologies CyprusMapOnto_vGizem CyprusMapOnto_vAli

Ontology Combining Different similarity measures combined to find mapping

candidates between two ontologies.

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Introduction - Case

Rules Different rules are determined in calculating

similarity measures and mapping the entities. We have tried to obtain the most appropriate

rule combination for our ontology combination case.

Comparison Prompt versus Similarity Approach

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Introduction - Platforms Protégé 2.1.2

Protégé is an ontology editor it provides graphical user interface (GUI) that models classes (domain concepts) and their attributes and relationships in ontology.

OWL plug-inPROMPT plug-in

Prompt is an ontology merging method for merge ontologies.

MatLab To perform our similarity approach algorithm.

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Cyprus Map Ontologies

CoverageLocation oriented

Coordinates Connections Location Specific Properties

No graphical information

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CyprusMapOnto_vGizem

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Cyprus Map Through Ontologies 9Gizem OLGU and Ali TUZEL

CyprusMapOnto_vGizem

Properties

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Cyprus Map Through Ontologies 10Gizem OLGU and Ali TUZEL

CyprusMapOnto_vGizem

Relations

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CyprusMapOnto_vAli

location

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CyprusMapOnto_vAli

Propertieslocation

Example 1:

city

Example 2:

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CyprusMapOnto_vAli

Relations historicalPlace

historicalPlaceType

isHistoricalPlaceTypeOf

Example 1:

city villagehasConnectionTo

hasConnectionTo

Example 2:

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Ontology Combination

Prompt Approach Similarity Approach

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PROMPT Approach

PROMPT starts with the similarity matches for the initial comparison. After the user selects an operation to perform

PROMPT not only points to the places where changes should be made, but also presents a list of actions to the user.

Summarizing, PROMPT gives iterative suggestions for concept merges and changes, based on linguistic and structural knowledge, and it points the user to possible effects of these changes.

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PROMPT Results

CyprusMapOnto_vAli: Class ID CyprusMapOnto_vGizem: Class ID

Location Location

mountain Mountain

City City

Lake Lake

Village Village

Bay Bay

Beach Beach

Cape Cape

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Similarity Approach

Similarity Measure

i: Ontology indexj: Entity indexeij: jth entity of ith ontologyk: Number of ruleswk: Weight of the specific kth similarity rule

(%0) 0 < wk < 1 (%100)(No similarity) 0 < sim < 1 (Identical)

Decision Treshold

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Cyprus Map Through Ontologies 18Gizem OLGU and Ali TUZEL

Similarity RulesRule Explanation Estimated weight

Rule 1 Common class IDsrdf:ID

%50

Rule 2 Common propertiesrdf:ID, rdfs:domain

%20

Rule 3 Common sub classesrdfs:subClassOf, rdf:resource,rdf:about

%10

Rule 4 Common super classesrdfs:subClassOf, rdf:resource,rdf:about

%10

Rule 5 Common instancesrdf:ID, property value

%10

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Similarity Calculation Using MATLAB

RETURNING VALUES

Class Pairs Having Similarity Over Treshold

Matched Class Similarity Measures

PARAMETERS

• Classes

• Class properties

• Sub classes

• Class relations

• Rule weights

• Treshold

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Similarity ResultsSimilarity Measure CyprusMapOnto_vAli CyprusMapOnto_vGizem

0.62109 location Location

0.50836 mountain Mountain

0.5072 city City

0.50697 lake Lake

0.50697 village Village

0.50396 bay Bay

0.50396 beach Beach

0.50396 cape Cape

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Demo

Prompt approach using Protege Similarity approach using MATLAB

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Conclusions

Two different ontologies can be combined using different approaches

Prompt versus SimilarityComparableFuture Works

RDB versus OntologyData: Unstructured

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Future Works

Optimization of rule weightsTraining Stage

Smart string comparisonThesaurus

Synonyms Singular – Plural etc.

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References1. Marc Ehrig and York Sure, “Ontology Mapping - An Integrated

Approach”, ESWS 2004, vol. 3053/2004, p. 76-91, April 21, 2004. Available at: http://www.aifb.uni-karlsruhe.de/WBS/ysu/publications/2004_esws_mapping.pdf.

2. N. F. Noy & M. A. Musen, “PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment”, Seventeenth National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, . 2000. Available at: http://smi-web.stanford.edu/pubs/SMI_Reports/SMI-2000-0831.pdf

3. Otology Editor, Protégé 2.1.2, http://protege.stanford.edu

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References4. Macromedia Fireworks MX,

http://www.macromedia.com/software/fireworks/

5. Bener Hakkı Hakeri, “Kıbrıs Türk Ansiklopedisi”, Book, vol. I, 1992.

6. Bener Hakkı Hakeri, “Kıbrıs Türk Ansiklopedisi”, Book, vol. II, 1992.

7. Zekai Altan, “Kuzey Kıbrısı Tanıyalım Gezelim Görelim”, Book, December 2000.

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Thank You

Any Questions??

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Question 1

Smart string comparison?

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Question 2

Standalone application instead of using MATLAB?

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