This is about application of visualization in Text mining. Text mining is an interesting topic in web Analytics, which is used to derive valuable information from text. The chapter starts with going through some existing visualization systems for text mining like Jigsaw, Trist etc... Trist seems to be interesting especially the icon size varies along the document size, large icons corresponds to large documents and other features like drag gable entities, clustering of documents makes it appealing for the user. Next the author comes up with some visualization tools used for document concordance ( "concordance : an alphabetical index of all the words in a text, showing those words in the contexts in which they appear") and word frequencies. Some visualization tools like concordancesoftware, SeeSoft, TextArc, etc... are presented. Among those TextArc looks very bad at interaction. The word tree visualization looks appealing and easy to visualize. The babynameswizard is interesting as it makes intelligent use of colors, pink for girl names and blue for boy names. Then the author presents some tools for Literature and Citation relationship. These tools are used to visualize how authors cite each other and to get the variation of importance of papers along time. Paperlens is an interesting tool, it shows user the citation frequency of all authors and popular topics of the year, It has different views for each. Visualization has great application in analyzing text at various forms, The visualizations should be in a way understandable to all kinds of users not just analysts who know what they are looking for.
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