Titlebook: Big Data Innovations and Applications; 5th International Co Muhammad Younas,Irfan Awan,Salima Benbernou Conference proceedings 2019 Springe

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MapReduce Join Across Geo-Distributed Data Centers, in such scenarios the cost for moving data among nodes connected via geographic links counterbalances the benefit of parallelization. In this paper the issues of running MapReduce Joins in a geo-distributed computing context are discussed. Furthermore, we propose to boost the performance of the Jo

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Mobile Device Identification via User Behavior Analysisr than 25 GB, which consists of accelerometer and gyroscope sensor data from 21 distinct devices is utilized. We employ different classification methods on extracted 40 features based on various time windows from mobile sensors. Namely, we use random forest, gradient boosting machine, and generalize

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Deep Learning Based Sentiment Analysis on Product Reviews on Twitterd convolutional neural network (CNN) have been utilized. In the empirical analysis, different subsets of Twitter messages, ranging from 5000 to 50.000 are taken into consideration. The prediction results obtained by deep-learning based schemes have been compared to conventional classifiers (such as,

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A Cluster-Based Machine Learning Model for Large Healthcare Data Analysisired output, which is Expanded Prostate Index Composite-26 (EPIC-26) domain scores. EPIC-26 is being used for assessing a range of HRQOL issues related to the diagnosis and treatment of prostate cancer. Different feature extraction methods are applied to extract features and the best method is the p

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The Information System for the Research in Carotid Atherosclerosiscreate a decision-making expert information system which should help decide about risk assessment in atherosclerosis of carotid artery. The idea of the system is based on differentiation of echogenicity grade according to Echo-Index value. In consequence, the system should classify the plaques into

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