Relevance Identification of Chinese News in the New Media Environment-Taking "Shandong Vaccine Event" as an Example

DOI

10.2991/eeeis-17.2017.72How to use a DOI?

Keywords

Maximum entropy, Chinese news relevance, Micro-blog, New media environment.

Abstract

In this paper, we construct the maximum entropy model, which improved the feature function and training set, to calculate the relevance degree of Chinese news and selected topics, and apply them to Chinese news event relevance recognition. According to the example of "Shandong vaccine event", the relevant data are obtained on the micro-blog platform. By selecting different numbers of features, this paper compare the maximum entropy model with the support vector machine (SVM), BP neural network, Bayes and K-means algorithm, which are four kinds of common text classification method of micro-average accuracy, by empirical analyzing.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Le SONG
AU  - Ming-Chun ZHENG
PY  - 2017/09
DA  - 2017/09
TI  - Relevance Identification of Chinese News in the New Media Environment-Taking "Shandong Vaccine Event" as an Example
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 490
EP  - 495
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.72
DO  - 10.2991/eeeis-17.2017.72
ID  - SONG2017/09
ER  -