An Optimized Solution for Ranking Based On Data Complexity
Sheenam Malhotra1, Williamjeet Singh2
1Sheenam Malhotra, Department of Computer Science and Engineering, Faculty of Engineering and Technology, Punjabi University, Patiala, Punjab, India.
2Williamjeet Singh, Department of Computer Science and Engineering, Faculty of Engineering and Technology, Punjabi University, Patiala, Punjab, India.
Manuscript received on 25 August 2019. | Revised Manuscript received on 07 September 2019. | Manuscript published on 30 September 2019. | PP: 4132-4139 | Volume-8 Issue-11, September 2019. | Retrieval Number: J96360881019/2019©BEIESP | DOI: 10.35940/ijitee.J9636.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud Computing is an emerging field with lot of possibilities for the maintenance at the Infrastructure Layer and Software Layer. A storage architecture is associated with two processes namely the storage and the retrieval process. The storage architecture plays a vital role in how quickly the data is retrieved. The retrieved data is presented as per the weight of the retrieved data. This paper presents a novel secure storage and the ranking mechanism for the documents for cloud. As no previous reference for any data is kept at the server, the data is encrypted based on the co-relation between the data files calculated by Cosine similarity. The ranking of the retrieved data is done through Supervised Machine learning mechanism. The evaluation of the parameters are done on the base of computation time and total number of true retrievals on multi-keyword search. Multiple dataset from Kaggle are used to perform and cross validate the proposed algorithm.
Keywords: Data Complexity Data Ranking Data Encryption Cosine Similarity
Scope of the Article: Data Analytics