The article illustrates a possible approach which combines existing technologies for Natural Language Processing (NLP), Knowledge Representation and Reasoning (KRR) and Data Visualization in a coherent Decision Support System (DSS). This approach is articulated in two main parts: the customization and integration of existing tools for automatic text annotation (at least linguistic, lexicographic and semantic) and the construction of a user-friendly and highly expressive GUI. The interface allows a user to: upload her/his own text, run the desired annotation tools, visually interact with the resulting multilayered network to: i) proof-read the results of the automatic annotations, ii) manually add missing elements and/or relations between elements and, finally, iii) formulate and verify specific interpretative hypotheses.
“Graphic Visualization in Literary Text Interpretation.”
Alessia Bellusci
2014-01-01
Abstract
The article illustrates a possible approach which combines existing technologies for Natural Language Processing (NLP), Knowledge Representation and Reasoning (KRR) and Data Visualization in a coherent Decision Support System (DSS). This approach is articulated in two main parts: the customization and integration of existing tools for automatic text annotation (at least linguistic, lexicographic and semantic) and the construction of a user-friendly and highly expressive GUI. The interface allows a user to: upload her/his own text, run the desired annotation tools, visually interact with the resulting multilayered network to: i) proof-read the results of the automatic annotations, ii) manually add missing elements and/or relations between elements and, finally, iii) formulate and verify specific interpretative hypotheses.File | Dimensione | Formato | |
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Paris2014_GraphicVisualizationLiteraryTextInterpretation.pdf
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