Application of Naive Bayesian Algorithms in E-mail Classification

In the context of the rapid development of today's society, high-tech information technology such as machine learning has played a very important role in promoting social, economic and technological development in all countries of the world. Bayesian classification algorithm is an important alg...

Full description

Saved in:
Bibliographic Details
Published in:Chinese Automation Congress (Online) pp. 3933 - 3938
Main Authors: Chen, Rui, Zhang, Cai-xia, Guo, Jing, Wang, Xiang-dong
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2019
Subjects:
Bayes methods
data mining
Data models
Dictionaries
email classification
Hidden Markov models
Machine learning
Monitoring
naive Bayesian algorithm
Postal services
Smart cities
text classification
ISSN:2688-0938
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract In the context of the rapid development of today's society, high-tech information technology such as machine learning has played a very important role in promoting social, economic and technological development in all countries of the world. Bayesian classification algorithm is an important algorithm in the field of machine learning and data mining. Naive Bayesian algorithm is a basic and simple classification algorithm in Bayesian classification algorithm. The naive Bayesian algorithm has the advantages of high stability, simplicity, high efficiency and strong theoretical foundation. The classification quality of the naive Bayesian algorithm much depends on the choice of construction methods and the nature and quantity of the classification data. In fact, many problems in our life can be attributed to classification problems, such as risk prediction, medical diagnosis, e-mail classification, fraud detection, etc. [1]. Here, I will mainly explain the principle of naive Bayesian algorithm, classification process, the evaluation of classification results, and apply this algorithm to e-mail classification tasks. At the same time, I list some related examples. Finally, I will summarize the naive Bayesian algorithm.
AbstractList In the context of the rapid development of today's society, high-tech information technology such as machine learning has played a very important role in promoting social, economic and technological development in all countries of the world. Bayesian classification algorithm is an important algorithm in the field of machine learning and data mining. Naive Bayesian algorithm is a basic and simple classification algorithm in Bayesian classification algorithm. The naive Bayesian algorithm has the advantages of high stability, simplicity, high efficiency and strong theoretical foundation. The classification quality of the naive Bayesian algorithm much depends on the choice of construction methods and the nature and quantity of the classification data. In fact, many problems in our life can be attributed to classification problems, such as risk prediction, medical diagnosis, e-mail classification, fraud detection, etc. [1]. Here, I will mainly explain the principle of naive Bayesian algorithm, classification process, the evaluation of classification results, and apply this algorithm to e-mail classification tasks. At the same time, I list some related examples. Finally, I will summarize the naive Bayesian algorithm.
Author Wang, Xiang-dong
Zhang, Cai-xia
Chen, Rui
Guo, Jing
Author_xml – sequence: 1
  givenname: Rui
  surname: Chen
  fullname: Chen, Rui
  organization: Foshan University,College of Automation,Foshan,China
– sequence: 2
  givenname: Cai-xia
  surname: Zhang
  fullname: Zhang, Cai-xia
  organization: Foshan University,College of Automation,Foshan,China
– sequence: 3
  givenname: Jing
  surname: Guo
  fullname: Guo, Jing
  organization: Foshan University,College of Automation,Foshan,China
– sequence: 4
  givenname: Xiang-dong
  surname: Wang
  fullname: Wang, Xiang-dong
  organization: Foshan University,College of Mathematics and Big Data,Foshan,China
BookMark eNotj8tKAzEUQKMo2NZ-gQj5gRlvbjJ5LMehVaHoRtflTibRyLxoitC_V7CrszoHzpJdjdMYGLsXUAoB7qGpG2W1lCWCcKV1zmAlLthSGLRCgVPyki1QW1uAk_aGrXP-BgCUQlUKFqyu57lPno5pGvkU-Suln8Af6RRyopHX_ed0SMevIfM08k0xUOp501POKZ6tW3Ydqc9hfeaKfWw3781zsXt7emnqXZEQ5LEITnkbjVOGfIW-xTZq1RkbtaHOtNF0qH2sADrvSWPboled-HM0OkHCyBW7---mEMJ-PqSBDqf9-Vj-Ar_BTKA
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CAC48633.2019.8997251
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 1728140943
9781728140940
EISSN 2688-0938
EndPage 3938
ExternalDocumentID 8997251
Genre orig-research
GroupedDBID 6IE
6IF
6IL
6IN
AAWTH
ABLEC
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
OCL
RIE
RIL
ID FETCH-LOGICAL-i203t-e94c8f7947ac52cb2bf64d78f67ad7bf7d26cf500dcca62bb2c4d14c86291a173
IEDL.DBID RIE
ISICitedReferencesCount 1
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000679040103181&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Aug 27 06:20:21 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i203t-e94c8f7947ac52cb2bf64d78f67ad7bf7d26cf500dcca62bb2c4d14c86291a173
PageCount 6
ParticipantIDs ieee_primary_8997251
PublicationCentury 2000
PublicationDate 2019-Nov.
PublicationDateYYYYMMDD 2019-11-01
PublicationDate_xml – month: 11
  year: 2019
  text: 2019-Nov.
PublicationDecade 2010
PublicationTitle Chinese Automation Congress (Online)
PublicationTitleAbbrev CAC
PublicationYear 2019
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0002314540
Score 1.7107242
Snippet In the context of the rapid development of today's society, high-tech information technology such as machine learning has played a very important role in...
SourceID ieee
SourceType Publisher
StartPage 3933
SubjectTerms Bayes methods
data mining
Data models
Dictionaries
email classification
Hidden Markov models
Machine learning
Monitoring
naive Bayesian algorithm
Postal services
Smart cities
text classification
Title Application of Naive Bayesian Algorithms in E-mail Classification
URI https://ieeexplore.ieee.org/document/8997251
WOSCitedRecordID wos000679040103181&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA61ePCk0opvcvBo7G6SzeO4lhZPpQeF3kqeutDuSh-C_94kW1oEL95CYAiZSTJJZr75AHjAhEprpUaGEooocRRp6jOEcXgbcCuD29CJbIJPJmI2k9MOeNxjYZxzKfnMPcVmiuXbxmzjV9lARJRnxEsfcc5arNb-PyXcU2IxuR1IJ8_kYFgOqWCExPytsCBa2V8kKsmHjE__N_oZ6B_AeHC6dzPnoOPqHijLQ-AZNh5OVDi14LP6dhEUCcvFexNe_R_LNaxqOEJLVS1g4r-MmUFJqg_exqPX4QvasSGgCmdkg5ykRviwfbgyBTYaa8-o5cIzrizXnlvMjC-yzAajMKw1NtTmQYYFtauckwvQrZvaXQJYGMdVuBiJqDKlpbBZZrzQRIpCqdxdgV6c_vyzLXgx3838-u_uG3ASNdwC9G5Bd7PaujtwbL421Xp1n6z0A0jrku4
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA6lCnpSacW3OXg0djdJN8lxLZaKdemhQm8lT11od6UPwX9vsl1aBC_eQmAIM3nMJJlvPgDuMKHCGKGQpoQiSixFiroIYezvBswI7zZURTbBsoxPJmLUAPdbLIy1tko-sw-hWf3lm1Kvw1NZhweUZ8BL7wXmrBqttX1R8ZFKKCdXw3TiSHR6aY_yhJCQweWXxEb6F41K5UX6R_8b_xi0d3A8ONo6mhPQsEULpOnu6xmWDmbSn1vwUX7bAIuE6ey99Pf-j_kS5gV8QnOZz2DFgBlygyqpNnjrP417A1TzIaAcR2SFrKCaO7-BmNRdrBVWLqGGcZcwaZhyzOBEu24UGT8tCVYKa2piL5N4w8uYkVPQLMrCngHY1ZZJHxrxYDKpBDdRpB1XRPCulLE9B62g_vRzU_JiWmt-8Xf3LTgYjF-H0-Fz9nIJDoO1N3C9K9BcLdb2Guzrr1W-XNxUM_YDIl6WNw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=Chinese+Automation+Congress+%28Online%29&rft.atitle=Application+of+Naive+Bayesian+Algorithms+in+E-mail+Classification&rft.au=Chen%2C+Rui&rft.au=Zhang%2C+Cai-xia&rft.au=Guo%2C+Jing&rft.au=Wang%2C+Xiang-dong&rft.date=2019-11-01&rft.pub=IEEE&rft.eissn=2688-0938&rft.spage=3933&rft.epage=3938&rft_id=info:doi/10.1109%2FCAC48633.2019.8997251&rft.externalDocID=8997251