Now a days web is growing very quickly, therefore it is important to search useful Patterns for web search document. The clustering of web search result has become a very interesting and popular research area to many organizations as it provides useful insights to information retrieval. Clustering of web search result system provides the search result for the user very concise and accurate, also provides reviews on them and locate specific information of interest. Clustering techniques can be used to organize retrieved results into a set of group based on their similarities. Several approaches existed for web document clustering using a suffix tree, but results show there is more research remains to be done. This paper presents a various approaches to Suffix Tree Cluster merge techniques to generate the informative, meaningful cluster and also compare some of the important cluster merging methods according to its performance . The method to merge clusters is used to sort out the problem of merging boundaries. Identical clusters are merged together based on a given estimation criterion until no more clusters can be merged. This survey aims to provide useful guidance for many applications where merging is having a remarkable impact on clustering.

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Web Information Retrieval Grouping Similarity Search Result Snippets