  Giving user a simple and well organized web search result has been a topic of
active information Retrieval (IR) research. Irrespective of how small or
ambiguous a query is, a user always wants the desired result on the first
display of an IR system. Clustering of an IR system result can render a way,
which fulfills the actual information need of a user. In this paper, an
approach to cluster an IR system result is presented.The approach is a
combination of heuristics and k-means technique using cosine similarity. Our
heuristic approach detects the initial value of k for creating initial
centroids. This eliminates the problem of external specification of the value
k, which may lead to unwanted result if wrongly specified. The centroids
created in this way are more specific and meaningful in the context of web
search result. Another advantage of the proposed method is the removal of the
objective means function of k-means which makes cluster sizes same. The end
result of the proposed approach consists of different clusters of documents
having different sizes.
