Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)

The application of LDA model on user profile

Authors
Yao Wei, Suling Jia, Qiang Wang, Hao Yu
Corresponding Author
Yao Wei
Available Online July 2017.
DOI
10.2991/essaeme-17.2017.389How to use a DOI?
Keywords
e-commerce, user profile technology, LDA model, Gibbs sampling algorithm, big data, data mining
Abstract

This paper puts forward the method of user profile technology based on LDA model. Abstracting the behavior and transaction information of the research object into the document, the LDA model can be trained and the research object can be described into the property tags, thereby to realize the user profile. The experimental results show that describing the research object as multidimensional labels based on LDA model can effectively characterize the research object and form their user profile.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
July 2017
ISBN
10.2991/essaeme-17.2017.389
ISSN
2352-5398
DOI
10.2991/essaeme-17.2017.389How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Yao Wei
AU  - Suling Jia
AU  - Qiang Wang
AU  - Hao Yu
PY  - 2017/07
DA  - 2017/07
TI  - The application of LDA model on user profile
BT  - Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/essaeme-17.2017.389
DO  - 10.2991/essaeme-17.2017.389
ID  - Wei2017/07
ER  -