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The main objective of this paper is to analyze the characteristics and features that affects the fluctuations of cryptocurrency prices and to develop aninteractive cryptocurrencychatbot for providing the predictive analysis of cryptocurrency prices. The chatbot is developed using IBM Watson assistant service. The predictive analytics is performed by analyzing the datasets of various cryptocurrencies and applying appropriate time series models. Time Series Forecasting is used for predicting the future values of the prices. Predictive models like ARIMA model is used for calculating the mean squared error of the fitted model. Facebook’s package prophet () which implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly and weekly seasonality are further used to predict cryptocurrency prices.

Skyline query is being widely adopted by the database community in today’s technological era. In a dynamic decision-making environment, the skyline query helps in producing effective results. Data produced in a dynamic decision-making scenario is prone to be affected by incomplete data. Executing the skyline query in a partially complete environment or incomplete data involves excessive pairwise comparisons which incurs degradation in the performance. This also affects the properties of skyline query. To address this challenge, we propose MIFCM (MICE Imputed Fuzzy C Means Clustering). Multivariate Imputation by Chained Equations (MICE) deals with data which has missing values. This proposed approach is a combination of MICE imputation and FCM clustering in order to improve the efficiency of skyline queries by reducing excess pairwise comparisons and search-time complexity of Skyline query. This manuscript captures our theoretical analysis and experimental results. From the experimental analysis, it is observed that the proposed approach significantly reduces the execution time for an incomplete dataset with an optimal result set size.

To classify the reliable resources accurately and perform a proactive fault tolerant scheduling in grid computing environment, a combination of support vector machine (SVM) with the quantum-behaved...