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Information Seminar Paper

Title

FINDING IMPORTANT CONCEPTS WITHIN ONTOLOGY

Pages

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Abstract

 THE INCREASING POPULARITY AND EXTENSION OF SEMANTIC WEB APPLICATIONS HAVE LED TO MYRIAD AMOUNTS OF RDF DATA AND ONTOLOGIES. THE LARGE-SCALE ONTOLOGY AND COMPLEX RDF DATASETS ARE ASSOCIATED BY SEVERAL SORTS OF COMPLEXITIES. IT IS SO DIFFICULT FOR USERS TO UNDERSTAND THESE DATA SETS EVEN IF USING VISUALIZATION TOOLS. IN ORDER TO PROMOTE THE PROCESS AND MAKE LARGE-SCALE ONTOLOGIES MORE UNDERSTANDABLE, RANKING ALGORITHMS HAVE BEEN USED. TO THIS END, IN THIS PAPER, WE INTRODUCE A NEURAL NETWORK-BASED RANKING APPROACH WHICH EXPLOITS CENTRALITY MEASURES, NUMBER OF CHILDREN, AND HIERARCHY LEVEL AMONG ONTOLOGY CONCEPTS. THE EVALUATION SHOWS HIGHER PERFORMANCE COMPARED TO EXISTING METHODS.

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    APA: Copy

    KARGAR, MOHAMMAD JAVAD, BABALOU, SAMIRA, DAVARPANAH, SEYYED HASHEM, Sarafraz, Pazire, & Algergawy, Alsayed. (2015). FINDING IMPORTANT CONCEPTS WITHIN ONTOLOGY. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/948796/en

    Vancouver: Copy

    KARGAR MOHAMMAD JAVAD, BABALOU SAMIRA, DAVARPANAH SEYYED HASHEM, Sarafraz Pazire, Algergawy Alsayed. FINDING IMPORTANT CONCEPTS WITHIN ONTOLOGY. 2015. Available from: https://sid.ir/paper/948796/en

    IEEE: Copy

    MOHAMMAD JAVAD KARGAR, SAMIRA BABALOU, SEYYED HASHEM DAVARPANAH, Pazire Sarafraz, and Alsayed Algergawy, “FINDING IMPORTANT CONCEPTS WITHIN ONTOLOGY,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2015, [Online]. Available: https://sid.ir/paper/948796/en

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