Study on Prediction Model of Personal Economic Level Based on Text Analysis Using Chinese Classified Lexicon
Year: 2019
Journal of Information and Computing Science, Vol. 14 (2019), Iss. 1 : pp. 44–51
Abstract
Obtaining economic situation of the group is a key step in understanding the socio-economic situation like the division of the rich and the poor. But the traditional way to obtain economic situation of the group is based on the survey data of professionals and mathematical models. Such methods are time- consuming and too dependent on professionals. Therefore, the use of data mining techniques to judge and predict the economic situation of the group came into being. Such methods are efficient that can overcome the shortcomings of the traditional methods. In this paper, we started by acquiring the individual's economic level and finally established a personal economic level prediction model. Through large-scale access to the individual's economic level, the economic level of the group can be obtained. We analyzed the Chinese text data published on the network by Individuals with logistic regression model to explore whether the above text data can reflect a person's economic status. The experimental results indicate that personal created textual data is able to forecast the individual's economic level accurately and certain categories of vocabulary have an impact on the individual's economic level.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22431
Journal of Information and Computing Science, Vol. 14 (2019), Iss. 1 : pp. 44–51
Published online: 2019-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 8