Titlebook: Advances in Data and Information Sciences; Proceedings of ICDIS Mohan L. Kolhe,Munesh C. Trivedi,Vikash Kumar Sing Conference proceedings 2

Genistein

Conference proceedings 2018 (ICDIS 2017), held at Indira Gandhi National Tribal University, India from November 3 to 4, 2017. The book covers all aspects of computational sciences and information security. In chapters written by leading researchers, developers and practitioner from academia and industry, it highlights the lat

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Harbor

Amir Ebrahimi Fard,Trivik Vermaphase data deduplication mechanism for text data. In the syntactic phase, a combination of clustering and Bloom Filter is used. In the semantic phase, a combination of SVD and WordNet synset is employed. Experimental results show the efficacy of the proposed system.

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2367-3370 (ICDIS 2017), held at Indira Gandhi National Tribal Universi.The book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Data and Information Systems (ICDIS 2017), held at Indira Gandhi National Tribal University, India from November 3 to

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https://doi.org/10.1007/978-3-030-43732-9lepsy states. In this paper, a fusion of signal and differential domain features are presented for the effective analysis and identification of epileptic EEG signals. The results of the proposed method for the identification of epilepsy in EEG signal are promising.

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爭(zhēng)吵加

https://doi.org/10.1007/978-3-031-30149-0niques to reduce the tags which are redundant and show low proportion of variance, hence reducing the computation complexity. Initial results prove that genomic tags give the better result in terms of finding similar type of movies, and give more accurate and personalized recommendation as compared to existing models.

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Refugees and the Misuse of the Criminal Lawoposed architecture has employed machine learning on a deep learning framework for analysis of pathological feature data that can be obtained from smartwatches worn by the patients with diabetes. The results showed that mist computing holds an immense promise for analysis of medical big data especially in telehealth monitoring of patients.

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