Intelligent spam filtering for massive short message stream
Purpose - The purpose of this paper is to provide an intelligent spam filtering method to meet the real-time processing requirement of the massive short message stream and reduce manual operation of the system. Design/methodology/approach - An integrated framework based on a series of algorithms is proposed. The framework consists of message filtering module, log analysis module and rules handling module, and dynamically filters the short message spam, while generating the filtering rules. Experiments using Java are used to execute the proposed work. Findings -The experiments are carried out both on the simulation model (off-line) and on the actual plant (on-line). All experiment data are considered in both normal and spam real short messages. The results show that use of the integrated framework leads to a comparable accuracy and meet the real-time filtration requirement. Originality/value - The approach in the design of the filtering system is novel. In addition, implementation of the proposed integrated framework allows the method not only to reduce the computational cost which leads to a high processing speed but also to filter spam messages with a high accuracy.
internet data management information technology mobile technology mobile networks programming and algorithm theory spam filtration massive data processing sampling algorithm