Ontology mapping for the semantic web

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Ontology mapping for the semantic web


  • 1.Mr. worawith sangkatip Student Master of Information Technology (IT) Faculty Informatics Mahasarakham University 1

2. Agenda Introduction Semantic Web Ontology Ontology Mapping Ontology Mapping Research Survey Ontology Mapping Techniques Conclusion Future Work 2 3. Introduction Present Web Technology and Semantic web Present Semantic web challenges Research Present Related Work Research Present Concept Research 3 4. Semantic Web Technology Web present Web pages are writing in html tag Html describes the syntax not the semantic Search engine return keyword and link Computer not understand the meaning behind information 4 5. Semantic Web Why Semantic Web ? the information that the user wants Computer understand the meaning behind information the semantic web as a component of Web 3.0 5 6. Semantic Web semantic of social connections 6 Source : Radar Networks & Nova Spivack, 2007 7. Semantic Web Semantic Web from the defines of Tim BernnersLee Semantic Web is a group of methods and technologies to allow machines to understand the meaning metadata is an important part the semantic web 7 8. Semantic Web 8 Source : The World Wide Web Consortium (W3C) Semantic Web stack 9. Ontology ontology is one component of the technology Semantic Web. A concept to describe the knowledge. Standard for understanding the meaning and scope of information of interest. Ontology is useful in the search better. With accuracy. 9 10. Ontology ontology can be used instead of semantic information to describe. RDF (Resource Description Framework) OWL (Web Ontology Language) adds semantic meaning 10 11. Ontology RDF (Resource Description Framework) a model for expressing metadata as triples (subject-predicate-object) Subject ObjectPredicate www.bicmsu.com BICsite-owner < rdf:RDF xmlns:rdf = http://www.w3.org/1999/02/22-rdf-syntax-ns# BIC (business intelligent center) : site-owner> 11 12. Ontology OWL (Web Ontology Language) OWL is a language that describes the data than the language RDF. the class (class), property (properties) and relationships. (Relationship). 12 Class1 Class3Class2 Properties: properties1: type1 properties2: type2 Class Hierachical ObjectProperty > 13. Ontology Mapping Why Ontology Mapping ? organization has its own ontology. use the shared ontology. problem in terms of data Replace or concept different. 13 14. Ontology Mapping What is Ontology Mapping Problem ? Specification of a conceptualization different specification of the terms in the domain and relations different 14 15. Ontology Mapping Type of Ontology Mapping 15 Ontology AlignmentOntology Mapping Ontology Merging 16. Ontology mapping Ontology mapping is important database integration, heterogeneous database retrieval (traditional) catalog matching (e-commerce) agent communication (theory only) web service integration (urgent) P2P information sharing (emerging) personalisation (emerging) 16 17. Ontology Mapping Research Semantic web Challenges [1] 17 A Classification of the Semantic Web Challenges 18. Ontology Mapping Research Research Classification of Ontology Mapping [2] Mapping Discovery Declarative formal representation of mappings Reasoning with mappings 18 19. Survey Ontology Mapping Techniques GLUE PROMPT QOM 19 20. GLUE [3] Machine learning techniques to find mappings. GLUE architecture consists of Distribution Estimator Similarity Estimator. Relaxation Labeler GLUE output's one to one correspondences between the taxonomies the ontologies . String similarity, structure and machine learning strategies. 20 Survey Ontology Mapping Techniques 21. PROMPT [4] Input: Two ontology's in OWL/ OKBC Output: Suggestions of mapping and a merging ontology based on the choice made by the user. iPROMPT : Interactive ontology merging tool. AnchorPROMT : Graph-based mappings to provide additional information for iPROMPT. PROMPTDiff : Compares different ontology versions by combining matchers in a fixed point manner. PROMPTFactor : Tool for extracting a part of an ontology. 21 Survey Ontology Mapping Techniques 22. QOM [5] String similarity, structure and instances. Input : Two OWL or RDFS ontology's with elements (e.g., classes, properties, instances) in the ontology's Output: One-to-one or one-to-none correspondences. 22 Survey Ontology Mapping Techniques 23. Conclusion Semantic web in a range of research and development. Semantic web research is innovative and important. Now in the era of web 3.0. 23 24. Future Work Research Ontology Mapping New Techniques Publish Research of survey ontology mapping techniques 24 25. References [1] Keyvanpour M, Hassanzadeh H, Mohammadizadeh B. "Comparative Classification of Semantic Web Challenges and Data Mining Techniques". Web Information Systems and Mining, 2009. Shanghai 2009. 200-203. [2] - N. Noy. Semantic Integration: A Survey of Ontology-based Approaches. Sigmond Record, Special Issue on Semantic Integration. 2004 25 26. Questions? Thank You. 26


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