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Hyunjang Kong,Myunggwun Hwang,Kwansang Na,Pankoo Kim

The Study on the Semantic Image Retrieval Using the Cognitive Spatial Relationships in the Semantic Web. Hyunjang Kong,Myunggwun Hwang,Kwansang Na,Pankoo Kim. Contents. Introduction Related Works Our Approach Test and Experimental Results Evaluations Conclusion. Introduction.

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Hyunjang Kong,Myunggwun Hwang,Kwansang Na,Pankoo Kim

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  1. The Study on the Semantic Image Retrieval Using the Cognitive Spatial Relationships in the Semantic Web Hyunjang Kong,Myunggwun Hwang,Kwansang Na,Pankoo Kim kisofire@chosun.ac.kr

  2. Contents • Introduction • Related Works • Our Approach • Test and Experimental Results • Evaluations • Conclusion kisofire@chosun.ac.kr

  3. Introduction • Huge number of data in the web • Image data is rapidly increasing • Object Based Spatial Relationships VS Cognitive Spatial Relationships • Building a Spatial Relationships Ontology kisofire@chosun.ac.kr

  4. Related Works • Information Retrieval System • Keyword Matching • Very important technique on the web environment • Process the various information items • Text Documents, Images, Sounds and etc. • Generally, accuracy is low kisofire@chosun.ac.kr

  5. Related Works • Ontology based Image Retrieval • Try to solve the heterogeneous between the terminologies • Need the extra works • Creating and Maintaining the ontologies • It is still unsuitable for the image retrieval system • Because it doesn’t consider the features of the images kisofire@chosun.ac.kr

  6. Related Works • The Spatial Description Logic • Region Connection Calculus : RCC-8 • Spatial representation is regular subsets of the topological space • Elementary binary relationships between the regions • PO, NTPP, TPP, EQ, TPP-1, NTPP-1, EC, DC kisofire@chosun.ac.kr

  7. Our Approach • Background Knowledge of the Cognitive Spatial Relationships kisofire@chosun.ac.kr

  8. Our Approach • Building Process of the Spatial Relationships Ontology • Defining the Cognitive Spatial Relationships • User Research • Using WordNet and Dictionary • OWL Representation kisofire@chosun.ac.kr

  9. Our Approach • Definition of the Cognitive Spatial Relationships kisofire@chosun.ac.kr

  10. Our Approach • User Research • 200 images • 10 people • Clustering the spatial words kisofire@chosun.ac.kr

  11. Our Approach • Architecture of the spatial ontology • Upper level • Basic spatial words level • Instance level kisofire@chosun.ac.kr

  12. Our Approach • WordNet and Dictionary Matching kisofire@chosun.ac.kr

  13. Our Approach • OWL Representation kisofire@chosun.ac.kr

  14. Test and Experimental Results • System Architecture • Contents provider interface • Ontology part • User interface kisofire@chosun.ac.kr

  15. Test and Experimental Results • Test Environment • Queries 1. Only one word query – e.g. swan 2. Two words query – e.g. swan and lake 3. Query containing the spatial relationships – e.g. swan in the lake 4. Natural Language query containing the spatial verbs – e.g. swimming swan 5. Natural Languages query containing the spatial verbs and proposition – e.g. swan swims in the lake kisofire@chosun.ac.kr

  16. Test and Experimental Results • Accuracy Measurement • Experimental Results kisofire@chosun.ac.kr

  17. Evaluations kisofire@chosun.ac.kr

  18. Evaluations kisofire@chosun.ac.kr

  19. Conclusion and Future Works • Definition of the Cognitive Spatial Relationships • Applying them to the Image Retrieval System • Still have Limitation : Semi-Automatic • Our study presents the vision of the semantic image retrieval and natural language query processing kisofire@chosun.ac.kr

  20. Does Anyone Have Any Questions? kisofire@chosun.ac.kr

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