Study on the Credibility Based on the Features of Agricultural Information

DOI

10.2991/ncce-18.2018.97How to use a DOI?

Keywords

agricultural webpage; SVM algorithm; credibility classifier.

Abstract

This paper based on agricultural information with timeliness, regional and other complex factors, proposed a method based on the features of agricultural webpage information to classify the credibility of agricultural webpage information. By constructing the model of the relationship between the features of agricultural information and the credibility of information, and combining with the SVM algorithm of machine learning, the credibility classifier is trained to predict and assess the credibility of agricultural webpage information. Experiments show that this method is feasible, as well as to evaluate the credibility based on information sources, has some advantages.

Copyright

© 2018, 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  - Yuyi Zhang
AU  - Yayao Zuo
AU  - Xiaobang Chen
PY  - 2018/05
DA  - 2018/05
TI  - Study on the Credibility Based on the Features of Agricultural Information
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 599
EP  - 603
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.97
DO  - 10.2991/ncce-18.2018.97
ID  - Zhang2018/05
ER  -