Anomaly detection is an important task for applications involving Big Data. Comparing with traditional method, anomaly detection in Big Data confronts growing amounts of data with high dimensionality and complex structures, which require more real-time analysis. This paper presents a fuzzy input-output system for anomalous data using electronic consumer records (ECR), a trapezium-cloud-map-filtration (TCMF) framework and a value mining model. ECRs are used to add or remove criteria based on consumers' consumption. In addition, MapReduce framework and trapezium clouds generated from each subsam...
