ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||7|
|Section||Session 3: Computer|
|Published online||05 September 2017|
Enhanced Microblog Network Representation with User-Generated Content
College of Computer, National University of Defense Technology, Changsha, China
The real-world networks are so sparse that only utilizing the limited edges cannot capture valuable user feature fully. However, the existing network embedding methods usually took the network structure into consideration merely. Therefore, inspired by the assumption that there exist latent relationships between those who generate similar text information, we proposed to enhance the original network structures by incorporating the latent relationships extracted from user-generated content into the raw network topology and furthermore to learn the representation for the revised network. Eventually, we evaluate our proposed method in two inference tasks and the experiment results demonstrate that the network representation generated by our enhanced network embedding method has a better performance than the baseline method on dataset provided by Sina Microblog.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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