Artificial learning approaches for the next generation web: Part II
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Published:
Oct 5, 2009
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Abstract
IN THIS PAPER WE PRESENT AN ONTOLOGY LEARNING TOOL FOR ASSEMBLING AND VISUALIZING ONTOLOGY COMPONENTS FROM A SPECIFIC DOMAIN FOR THE SEMANTIC WEB. THE FOCAL POINT OF THE PAPER IS ON SELF-ORGANIZING MAPS (SOM). SOME OF THEIR PROPERTIES AND THE LEARNING ALGORITHM ARE DESCRIBED. PRACTICAL SUGGESTIONS ON HOW TO CREATE GOOD MAPS ARE ALSO PRESENTED. RELATED WORK IS THEN REPORTED. FINALLY, THE RELATION OF SOM WITH THE SEMANTIC WEB ONTOLOGY CREATION PROCESS, AS WE ENVISION IT, IS INTRODUCED
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GUTIÉREZ PULIDO, J. R., CABELLO ESPINOZA, M., ANDRADE ARÉCHIGA, M., HERRERA MORALES, J. R., LEGRAND, S., & ELLIMAN, D. (2009). Artificial learning approaches for the next generation web: Part II. Ingeniería Investigación Y Tecnología, 9(002). Retrieved from https://journals.unam.mx/index.php/ingenieria/article/view/13494