Monday, November 28, 2011


This paper discuss about diffrent types of visulization used in analysis of documents or texts. Primary focus of this paper is to illustrate understanding of text collection from analytical point of view. And to achieve this author discuss about application of visualization in text mining, forming concordances and relationships between words and their usage in the language and lexical ontologies. Text mining focus on identifying important entities within the text and showing connections among them. Examples to illustrate this includes TAKMI text mining system, JIGSAW system, BETA system and triage system. Visualizing Concordance And Word Frequencies involves placing the word of interest in the center with related text around sorted in some way. I particularly like TextArc visualization as it's coxcomb-type radial visualization is intuitive as well as flexible to suit user's expectations and also provide an effective visual display of text treemap and word linkage in a document. Tag cloud visualization and Name voyager has been discussed in class which analyze a collection of texts by extracting concordance. I agree with notion that categorical nature of text and its high dimensionality, make
it very challenging to display content graphically as they have no inherent ordering. At last, author discuss about literary and citation analysis to assess the importance of the authors, the papers, and the topics in the field. Node-links graph and PaperLens interface explains the concept. Overall, its a very informative read and examples cited makes it easy to understand the underlying concept.