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GLOBALSOFT TECHNOLOGIES 
IEEE PROJECTS & SOFTWARE DEVELOPMENTS 
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE 
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS 
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com 
A Graph Derivation Based Approach for Measuring and 
Comparing Structural Semantics of Ontologies 
Abstract 
Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art 
approaches for measuring ontologies neglects the problems of both the polymorphism of ontology 
representation and the addition of implicit semantic knowledge. One way to tackle these problems is to 
devise mechanism for ontology measurement that is stable, the basic criteria for automatic 
measurement. In this paper, we present a graph derivation representation based approach (GDR) for 
stable semantic measurement, which captures structural semantics of ontologies and addresses those 
problems that cause unstable measurement of ontologies. This paper makes three original 
contributions. First, we introduce and define the concept of semantic measurement and the concept of 
stable measurement. We present the GDR based approach, a three-phase process to transform an 
ontology to its GDR. Second, we formally analyze important properties of GDRs based on which stable 
semantic measurement and comparison can be achieved successfully. Third but not the least, we 
compare our GDR based approach with existing graph based methods using a dozen real world exemplar 
ontologies. Our experimental comparison is conducted based on nine ontology measurement entities 
and distance metric, which stably compares the similarity of two ontologies in terms of their GDRs. 
Existing system 
Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art 
approaches for measuring ontologies neglects the problems of both the polymorphism of ontology 
representation and the addition of implicit semantic knowledge. One way to tackle these problems is to 
devise mechanism for ontology measurement that is stable, the basic criteria for automatic 
measurement.
Proposed system 
In this paper, we present a graph derivation representation based approach (GDR) for stable semantic 
measurement, which captures structural semantics of ontologies and addresses those problems that 
cause unstable measurement of ontologies. This paper makes three original contributions. First, we 
introduce and define the concept of semantic measurement and the concept of stable measurement. 
We present the GDR based approach, a three-phase process to transform an ontology to its GDR. 
Second, we formally analyze important properties of GDRs based on which stable semantic 
measurement and comparison can be achieved successfully. Third but not the least, we compare our 
GDR based approach with existing graph based methods using a dozen real world exemplar ontologies. 
Our experimental comparison is conducted based on nine ontology measurement entities and distance 
metric, which stably compares the similarity of two ontologies in terms of their GDRs. 
SYSTEM CONFIGURATION:- 
HARDWARE CONFIGURATION:- 
 Processor - Pentium –IV 
 Speed - 1.1 Ghz 
 RAM - 256 MB(min) 
 Hard Disk - 20 GB 
 Key Board - Standard Windows Keyboard 
 Mouse - Two or Three Button Mouse 
 Monitor - SVGA 
SOFTWARE CONFIGURATION:- 
 Operating System : Windows XP 
 Programming Language : JAVA 
 Java Version : JDK 1.6 & above.
2014 IEEE JAVA DATA MINING PROJECT A graph derivation based approach for measuring and comparing structural semantics of ontologies

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2014 IEEE JAVA DATA MINING PROJECT A graph derivation based approach for measuring and comparing structural semantics of ontologies

  • 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com A Graph Derivation Based Approach for Measuring and Comparing Structural Semantics of Ontologies Abstract Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art approaches for measuring ontologies neglects the problems of both the polymorphism of ontology representation and the addition of implicit semantic knowledge. One way to tackle these problems is to devise mechanism for ontology measurement that is stable, the basic criteria for automatic measurement. In this paper, we present a graph derivation representation based approach (GDR) for stable semantic measurement, which captures structural semantics of ontologies and addresses those problems that cause unstable measurement of ontologies. This paper makes three original contributions. First, we introduce and define the concept of semantic measurement and the concept of stable measurement. We present the GDR based approach, a three-phase process to transform an ontology to its GDR. Second, we formally analyze important properties of GDRs based on which stable semantic measurement and comparison can be achieved successfully. Third but not the least, we compare our GDR based approach with existing graph based methods using a dozen real world exemplar ontologies. Our experimental comparison is conducted based on nine ontology measurement entities and distance metric, which stably compares the similarity of two ontologies in terms of their GDRs. Existing system Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art approaches for measuring ontologies neglects the problems of both the polymorphism of ontology representation and the addition of implicit semantic knowledge. One way to tackle these problems is to devise mechanism for ontology measurement that is stable, the basic criteria for automatic measurement.
  • 2. Proposed system In this paper, we present a graph derivation representation based approach (GDR) for stable semantic measurement, which captures structural semantics of ontologies and addresses those problems that cause unstable measurement of ontologies. This paper makes three original contributions. First, we introduce and define the concept of semantic measurement and the concept of stable measurement. We present the GDR based approach, a three-phase process to transform an ontology to its GDR. Second, we formally analyze important properties of GDRs based on which stable semantic measurement and comparison can be achieved successfully. Third but not the least, we compare our GDR based approach with existing graph based methods using a dozen real world exemplar ontologies. Our experimental comparison is conducted based on nine ontology measurement entities and distance metric, which stably compares the similarity of two ontologies in terms of their GDRs. SYSTEM CONFIGURATION:- HARDWARE CONFIGURATION:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 256 MB(min)  Hard Disk - 20 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse  Monitor - SVGA SOFTWARE CONFIGURATION:-  Operating System : Windows XP  Programming Language : JAVA  Java Version : JDK 1.6 & above.