Research on Intelligent Acceleration Algorithm for Big Data Mining in Communication Network Based on Support Vector Machine

Abstract

As a budding technology, big data’s technical implementation and commercial application are in the exploratory stage. With the increasing development of network and communication technology, a large amount of information is pouring in. How to effectively select the required information has become a more and more prominent problem. Data mining is a data processing technology developed to meet this need. Support vector machine is a new technology in data mining. It is a new tool to solve machine learning problems with the help of optimization methods. Among them, it focuses on the support vector machine, including the development history and present situation of support vector machine, the main basic concepts and research contents. On this basis, it studies various training algorithms of support vector machine which are relatively common at present, and compares their advantages and disadvantages. Big data has various data types, forming a data stream with various attributes. As we all know, data source classification based on batch processing can improve the query speed, but it still can’t meet the demand of real-time query. Therefore, feature selection mechanism is usually introduced in the process of data mining modeling to reduce its load. However, when faced with the query of high-dimensional data, the query space grows exponentially, which is difficult to realize. Therefore, this paper proposes the efficiency of an intelligent acceleration algorithm for big data mining based on vector machine communication network.