This paper deals with the concept of TileBars. TileBars demonstrate the usefulness of explicit term distribution information in Boolean –type queries.
The paper also has a discussion on rankings. The author says that the ranking should provide users results which are quite informative and easily comprehendible. The standard approach to document ranking is opaque, users are unable to see what role their query terms played in the ranking of the retrieved documents. An ordered list of titles and probabilities is under informative. The TileBars are compactly arranged and indicate relative document length, query term frequency, and query term distribution. The technique helps in ranking of the documents based on various features of the term sets.
According to me TileBars is certainly an effective way of visualization. Every document is represented using rectangles and each column represents sections. The frequency is represented using color coding. And each row in the rectangle represents the visualization for a word in the multi-word search query.
I found the figures 4 and 5 quite interesting. They show the result of a query on three term set in a version of the interface that allows the user to restrict which documents are displayed according to several constraints like minimum number of hits for each term set, minimum distribution etc.
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