This paper mainly argues for making use of text structure when retrieving from full text documents, and presents a visualization paradigm, called TileBars. TileBars seem to be a analytical tool for understanding the results of various types of queries. This approach to visualization of the role of the query terms within the retrieved documents. When we make a query there can multiple documents that can be of interest with further concentration of how similar or the frequency or the ranking of the occurrences.
Figure 3 given an inital preview of what exactly TitleBars is about. It provides a compact and informative iconic representation of the documents' contents with respect to the query terms.
TileBars allow users to make informed decisions about not only which documents to view, but also which passages of those documents, based on the distributional behavior of the query terms in the documents.
The three main aspects are :
1) The relative length of the document,
2) The frequency of the term sets in the document, and
3) The distribution of the term sets with respect to the document and to each other.
The bars are not ordered in any fashion but they just have a number. Seeing the bar it is easy to compare the documents and also the occurrences(how exact match). One drawback would if we have a lot of documents having the query hits with variation that is difficult to represent by the gradient of (black to grey to white). Also as we increase the search set(1,2,3..) the bar will be divided and again hard to compare .
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