Study of Network Information Encountering Influence Factors for Undergraduate Group Based on Support Vector Machine postprint

Abstract: [Purpose/significance] In the current Web 2.0 network environment, information encountering is one important method to get information for the undergraduate group. This study is of important significance of improving the ability of information encountering and information literacy for university students.[Method/process] Aiming at university students, this paper studies the sensitive influence factors of information encountering in the environment of network. Specifically speaking, this paper uses information gain to analyze the correlation between each influence factor and information encountering frequency, and then builds the model of sensitive influence factor. Furthermore, support vector machine(SVM) is introduced to establish the prediction model for information encountering frequency.[Result/conclusion] There exists 10 most sensitive influence factors for information encountering which are located in four dimensions including information user, encountering information, network environment and situation factors. The predicted classification accuracy can reach 82.96%, which demonstrates SVM works well to predict information encountering frequency.