Research on detection methods based on Doc2vec abnormal comments-Reference-Cited by-同舟云学术

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Research on detection methods based on Doc2vec abnormal comments

Published:2018-09 Issue: Volume:86 Page:656-662
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Chang Wenbing,Xu Zhenzhong^ORCID,Zhou Shenghan,Cao Wen^ORCID

Funder

National Natural Science Foundation of China

Aviation Science Foundation of China

Technical Research Foundation and the Graduate Student Education & Development Foundation of Beihang University

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference20 articles.

1. Measures of abnormal user activities in online comments based on cosine similarity;Kim;J. Korea Inst. Inform. Secur. Cryptol.,2014

2. Sampling utterances and grammatical analysis revised (SUGAR): New normative values for language sample analysis measures;Pavelko;Lang. Speech Hearing Serv. Schools,2017

3. An automated system for grammatical analysis of Twitter messages. A learning task application;Oussalah;Knowl. Based Syst.,2016

4. Who should comment on this pull request? Analyzing attributes for more accurate commenter recommendation in pull-based development;Jiang;Inform. Softw. Technol.,2017

5. Detection of review spam: A survey;Heydari;Exp. Syst. Appl.,2015

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