We refer this kind of information needs as aspect topics. The answer of an aspect topic consists of more than one related piece of information. Classification is the most primitive and common activities of human being, which consists of sorting like things into categories. The popular application of categories proves it to be an effective way to help people manage their information. The basic idea behind the two structured deliveries is to classify the retrieved documents.
Cluster analysis is a tool to reveal structure and relations in the data.
If the extracted topics could map to potential aspects of a topic this structure will help users for their aspect seeking task. Here, the extracted topics act as categories, the retrieved documents will be classified into their closest categories. A cluster description was formed from the ten highest-weighted terms from the cluster vector, the five most frequent words pairs from all documents in the cluster, and the titles of the three documents in the cluster that were most similar to the query. Figure 1 shows an interface to present cluster structure. The interface is divided into two panels.