Quality Assessment Method of Web Documents Based on Random Forest

DOI

10.2991/icmmcce-17.2017.190How to use a DOI?

Keywords

Web document; quality assessment; LDA topic model; random forest

Abstract

This paper proposes a method based on the method of Random Forest (RF) for better assessing quality of web documents, and formulates a novel quality evaluation index system including features of organization structure, network access and content. In order to extract the content feature of a document, a topic coverage degree calculation model based on LDA is put forward. Finally, it conduct some experiments on two document sets: Wikipedia and Baidu Encyclopedia, and precision rate, recall rate and F-Measure are used to verify the validity of the proposed quality assessment method. Experimental results show that the proposed evaluation index system and the RF-based quality assessment method can achieve good performance and advantages.

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  - Li He
AU  - Li Tang
AU  - Ning Wang
PY  - 2017/09
DA  - 2017/09
TI  - Quality Assessment Method of Web Documents Based on Random Forest
BT  - Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017)
PB  - Atlantis Press
SP  - 1058
EP  - 1065
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmcce-17.2017.190
DO  - 10.2991/icmmcce-17.2017.190
ID  - He2017/09
ER  -