Internet bad information detection based on Bert model

Xin CAI

doi:10.11959/j.issn.1000-0801.2020303

您当前的位置：

首页 >

文章列表页 >

Internet bad information detection based on Bert model

Topic:Information Security | 更新时间：2024-06-05

- Internet bad information detection based on Bert model
- Telecommunications Science Vol. 36, Issue 11, Pages: 121-126(2020)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020303
  CLC： TP393
- Published Online：2020-11，
  
  Published：20 November 2020
- 稿件说明：
移动端阅览
Xin CAI. Internet bad information detection based on Bert model[J]. Telecommunications science, 2020, 36(11): 121-126.
DOI：

Xin CAI. Internet bad information detection based on Bert model[J]. Telecommunications science, 2020, 36(11): 121-126. DOI： 10.11959/j.issn.1000-0801.2020303.

摘要

针对互联网不良信息检测这一业务场景，探讨了基于网站文本内容进行检测的方法。回顾了经典的文本分析技术，重点介绍了Bert模型的关键技术特点及其两种不同用法。详细描述了利用其中的特征提取方法，进行网站不良信息检测的具体实施方案，并且与传统的TF-IDF模型以及word2vec+LSTM模型进行了对比验证，证实了这一方法的有效性。

Abstract

In view of the business scenario of bad information detection on the internet

the method of detection based on the text content of the website was discussed .Classical text analysis techniques were reviewed.The key technical features and two different usages of Bert model were introduced.The specific implementation scheme of using the feature extraction method to detect website bad information was described in detail

and was compared with the traditional TF-IDF model and word2vec+LSTM model.The validity of this method is verified.

关键词

Keywords

references

蔡鑫 , 娄京生 . 基于LSTM深度学习模型的中国电信官方微博用户情绪分析 [J ] . 电信科学 , 2017 , 33 ( 12 ): 136 - 141 .

CAI X , LOU J S . Sentiment analysis of telecom official mi-cro-blog users based on LSTM deep learning model [J ] . Tele-communications Science , 2017 , 33 ( 12 ): 136 - 141 .

SCOTT D . Indexing by latent semantic analysis [J ] . Journal of the American Society for Information Science , 1990 ( 41 ):6.

BLEI D M , NG A Y , JORDAN M I , et al . Latent dirichlet Allocation [J ] . Journal of Machine Learning Research , 2012 ( 3 ): 993 - 1022 .

MIKOLOV T , CHEN K , CORRADO G , et al . Efficient estimation of word representations in vector space [J ] . arXiv:1301.3781 , 2013

PETERS M , NEUMAN M , IYYER M , et al . Deep Contextualized Word Representations [J ] . arXiv:1802.05365 , 2018

RADFORD A , SALINMANS T . Improving language understanding by generative pre-training [J ] . 2018

DEVLIN J , CHANG M , LEE K , et al . BERT:pre-training of deep bidirectional transformers for language understanding [J ] . arXiv:1810.04805 , 2018

Views

945

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A hybrid model for smart grid theft detection based on deep learning

Optimal active defense decision model of wireless communication network under APT attack

Low complexity radar signal classification based on spectrum shape

Face recognition algorithm based on attractive local second gradient contours

Smart prediction of the complaint hotspot problem in mobile network

Related Author

Yaoyuan LIANG

Jun ZHANG

Yinling LIAO

Jincan LI

Bing WANG

Danni WANG

Meng MENG

Fuliang ZHANG

Related Institution

Guangxi Power Grid Co., Ltd.

Wuzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd.

School of Communication and Information Engineering, Beijing University of Posts and Telecommunications

National Innovation Institute of Defense Technology, Academy of Military Science

Jiangsu Branch of China Telecom Co., Ltd.

⁰