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Ontological Tree Generation for Enhanced Information Retrieval
2013
International Journal of Artificial Intelligence & Applications
Information visualization seeks to leverage human visual processing to make sense of abstract information. One particularly rich class of information structures ripe for visualization are those representable as graphs (i.e. nodes and edges), including organization charts, website linkage, and computer networks. In this paper we propose a methodology to extract information from big data and convert it into a human comprehensible format of graphs to give the reader an objective overall idea of
doi:10.5121/ijaia.2013.4405
fatcat:xxnqyw4abnhsxguxxeppcpfpru