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As the digital data increases on servers different researcher have focused on this field. As various issues are arise on the server such as data handling, security, maintenance, etc. In this paper document retrieval was proposed that efficiently the fetch document as per query. Here hash based indexing of the dataset document was done by utilizing term features. In order to provide privacy for the terms each of this is identified by a unique number and each document has its hash index key for identification. Experiment was done on real and artificial dataset. Results shows that NDCG, precision, recall parameter of the work is better as compare to previous work on different size of datasets. Conclusion With the drastic increase of the digital text data on the servers, libraries it is important for researcher to work on it. Considering this fact work has focus on one of the issue of the document retrieval. Here many researchers has already done lot of work but that is focus only on the content classification where in this work document are classify. Proposed work has increase the retrieval efficiency of the work in all different evaluation parameters. So use of hash based indexing provide privacy with efficiency for document retrieval. As there is always work remaining in every because research is a never ending process, here one can implement similar thing for different other language.
IEEE Base Paper | |||
Doc | Synopsis and model of working | ||
Source Code | Complete Code files |