User Modeling on Social Networks--Using User Tags and Weibo Content for User Modeling
- https://doi.org/10.2991/cmsa-18.2018.1How to use a DOI?
- user modeling; user tag; vector space model; feature extraction
User-generated content is of great significance for user modeling and user interest mining. This paper defines a microblog user model which combining weibo content and tags with vector space model(VSM) representation. The user model consists of two parts, one part, user interest representation based on weibo content: pretreatment, feature extraction, and then compute the characteristic value with TF-IDF method, after that, the user's weibo content is expressed by VSM; Another part, user interest representation based on user tags: feature extraction and word frequency method for computing the characteristic value and user tags are expressed by VSM. Finally, the resulting user model can be obtained by combining the two parts mentioned above.
- © 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/).
Cite this article
TY - CONF AU - Xuehua Chi PY - 2018/04 DA - 2018/04 TI - User Modeling on Social Networks--Using User Tags and Weibo Content for User Modeling BT - Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018) PB - Atlantis Press SP - 1 EP - 3 SN - 1951-6851 UR - https://doi.org/10.2991/cmsa-18.2018.1 DO - https://doi.org/10.2991/cmsa-18.2018.1 ID - Chi2018/04 ER -