We present an efficient indexing method called clustered SS-tree for high dimensional database for approximate nearest neighbor queries. The main idea of this approach is to cluster data before creating the index and then apply filtering of index nodes based on angle property in high dimension for efficient searching for clustered SS-tree provides several orders of magnitude better performance than exact nearest neighbor search of SS-tree and VA file.