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Web mining, an indispensable branch of data mining is to mine large web data repositories in order to produce results that can be used in these design tasks. Owing to lack of heterogeneity in structure of web data there needed for the evolution of web mining. Web content mining is analogous but different from data mining and text mining additionally the amount of data/information on the Web is huge and still growing rapidly. The issues allied with web content mining is the critical decision-making process. In our previous approach the prime demerits are that First top two ranking sentences are taken to be considered for retrieval of information; consequently due to the redundancy fact clustering accuracy was to bare minimum level. In our proposed approach the documents are clustered according to category based on Fuzzy category based Aggregation Algorithm. Resultantly User pertinent documents are retrieved based on query weighting methodology. The simulation results portrays that our proposed approach facilitates effectively when applied with large set of documents moreover illustrates superior optimization results in terms of accuracy too.