  With the huge upsurge of information in day-to-days life, it has become
difficult to assemble relevant information in nick of time. But people, always
are in dearth of time, they need everything quick. Hence clustering was
introduced to gather the relevant information in a cluster. There are several
algorithms for clustering information out of which in this paper, we accomplish
K-means and K-Medoids clustering algorithm and a comparison is carried out to
find which algorithm is best for clustering. On the best clusters formed,
document summarization is executed based on sentence weight to focus on key
point of the whole document, which makes it easier for people to ascertain the
information they want and thus read only those documents which is relevant in
their point of view.
