This is a very interesting research paper that discusses about a novel approach of assessing information from huge chunk of textual data. For this, authors have created a tool Jigsaw which is used to visually represent the textual content in the documents.
I certainly feel that this is a very interesting topic of text summarization , especially today when gazillion bytes of data is created everyday. There are number of tools available today for text summarizing, however representing the textual data into sort of visualizations would be indeed a very good idea!
Authors discusses that it is possible to break down any document into perceptive visual forms like graph, tables, scatter view, text view etc. This is helpful in the field of data analytics where the data is in the form of text and not represented as a reports.
In the end, paper also discusses the limitation of such system that it's difficult to evaulate it from usability perspective and trial use by real analysts. Another challenge that it faces is the scalability as for larger report collections in which the number of entitites in a category can grow into the thousands or beyond. Probably their approach needs some form of dynamic update and filtering.
Overall I feel that the Jigsaw is not a substitute for careful analysis of the data reports, however it certainly gives some insights about visual indexes that present entity relations in forms that are easily perceieved.
0 comments:
Post a Comment