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- W2527884055 abstract "In the Big Data era, the visualization of large datasets is becoming an increasingly relevant task due to the greatimpact that data have from a human perspective. Since thevisualization is the closer phase to the users within the datalife cycles phases, there is no doubt that an effective, efficientand impressive representation of the analyzed data may resultas important as the analytic process itself. Starting fromprevious experiences in importing, querying and visualizingWordNet database within Neo4J and Cytoscape, this work aimsat improving the WordNet Graph visualization by exploitingthe features and concepts behind tag clouds. The objectiveof this study is twofold: firstly, we argue that the proposedvisualization strategy is able to put order in the messy anddense structure of nodes and edges of large knowledge bases asWordNet, showing as much as possible information from thisknowledge source and in a clearer way, secondly, we thinkthat the tag cloud approach applied to the synonyms ringsreinforces the human cognition in recognizing the differentusages of words in natural languages like English. In thisregard, we also propose a formal strategy in order to evaluatethe information perception in the use of our methodology bymeans of a questionnaire asked to a group of users. Finally, wecompare these results with those resulting from the adoption ofwell known representations of WordNet within existing GUIs." @default.
- W2527884055 created "2016-10-14" @default.
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- W2527884055 date "2016-06-01" @default.
- W2527884055 modified "2023-09-26" @default.
- W2527884055 title "Improving the Visualization of WordNet Large Lexical Database through Semantic Tag Clouds" @default.
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- W2527884055 doi "https://doi.org/10.1109/bigdatacongress.2016.14" @default.
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