The chapter gives an overview of a wide array of tools used in the area of Information Visualization of text.
The tools are meant for different purposes which tells us that mining and analysis of text from a source or combined sources has the potential to expose hidden meaning or connections between them. There are some tools which enable you to find connections between different entities scattered across different documents. The TRIST tool is really interesting to see because it supports so many features and views to help to user in textual analysis. This article also goes to the domain of analyzing work frequencies and literature and their citation relationships.
I think this research makes a lot of sense as literature whether it be scientific or philosophical, is present in digital format. So there is more data for these tools to work with. One very important thing to observe is that no tools cited in this article capture context of words. Obviously this is not in the scope of the document but I can see it as a potential extension for some of these tools. It would be interesting to see if these tools can be made intelligent and also can help not just in textual analysis but also in text production for instance. Based on the trends of words and the contexts that they are used in, we should be able to provide the writer with a suggestions of word that he/she can use in their literature.
I think the article is very well supported with illustrations. I found the 2007 State of Union address and the Name voyager examples as really cool. I felt that the paper was well organized especially regarding how the tools were ordered and presented with their application areas.
0 comments:
Post a Comment