Application of LDA Topic Model in E-Mail Subject Classification

DOI

10.2991/tlicsc-18.2018.24How to use a DOI?

Keywords

LDA topic model, E-mail, TF-IDF, Text classification.

Abstract

Text classification is an important research direction in the field of natural language processing. With the development of Internet, the use of e-mail is becoming more and more common. It is very important to quickly understand the subject and content of an e-mail in a mailbox. For example, when the police handle a case and face this demand, the intelligent processing of text information by computer has been extensively studied. This paper proposes an application of mail classification based on LDA topic model, which combines information extraction, information retrieval and natural language processing. SVM classifier is used, and TF-IDF technology, which is a technical evaluation method for the classification of this application, is also proposed. It is believed that LDA has a certain effect in mail classification, and the uncertainty and subjectivity in LDA classification are also proposed.

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  - Hechen Gong
AU  - Fucheng You
AU  - Xinxin Guan
AU  - Yue Cao
AU  - Shuren Lai
PY  - 2018/12
DA  - 2018/12
TI  - Application of LDA Topic Model in E-Mail Subject Classification
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 144
EP  - 150
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.24
DO  - 10.2991/tlicsc-18.2018.24
ID  - Gong2018/12
ER  -