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Visualized comparison for CFP datasets by structure identification and ontology

This paper proposes a method to visualize relations and keywords of two Call For Paper (CFP) datasets for comparison or trend research. Based on our previous works on information extraction from CFP files and trend visualization system (FACT-Graph), this paper describes the contribution and usefulness of the different methods of data input into the visualization system. Using two CFP datasets from two academic societies in order to support our theory, we compare three input data processes from basic plain text data to structured data made from selected relevant data along with the contribution of external data from ontology models.