Hybrid Approach Using Fuzzy Logic and MapReduce to Achieve Meaningful Used Big Data - Almukahel, Ikhlas; Alzyadat, Wael; Alfayomi, Mohamad (International Journal of Engineering and Technology, 2019)
Big data faces many challenges from different aspects; these challenges are represented in characteristics, such as volume, velocity, variety, and value. Preprocessing and analyzing big data are important issues to acquire quality information toward accurate values for correct decision making. Quality data taxonomy points to two basic actions to ensure that data is meaningful and predictive. Consequently, a hybrid approach using fuzzy logic and MapReduce is utilized to produce a new version of MapReduce which consist of four layers. Data collection is achieved in the first layer. The second layer consist of preprocessing data, where semi-structured data is treated to clean up and obtain the map function to acquire relationships. The third layer includes the application of fuzzy controller as well as classification to generate rules. Finally, in the fourth and last layer, data reduction and classification are carried out to achieve a meaningful and predictive outcome. The result showed the efficiency of the approach through Sensitivity = 80%, Specificity = 86% and F-measure= 2.5 that were validated in TREC conference website. The hybrid approach treating the 4Vs towards achieving meaningful which has positive effect support doctor to take the right decision.Â Â
Keywords: Big Data; MapReduce; Meaningful; Predictive; Fuzzy Logic Controller.