Application of LDA Topic Model in E-Mail Subject Classification
Hechen Gong, Fucheng You, Xinxin Guan, Yue Cao, Shuren Lai
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.24How to use a DOI?
- LDA topic model, E-mail, TF-IDF, Text classification.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/tlicsc-18.2018.24 DO - https://doi.org/10.2991/tlicsc-18.2018.24 ID - Gong2018/12 ER -