Improving Microblog Retrieval from Exterior Corpus by Automatically Constructing Microblogging Corpus
Abstract
A large-scale training corpus consisting of microblogs belonging to a desired category is important for high-accuracy microblog retrieval. Obtaining such a large-scale microblgging corpus manually is very time and labor-consuming. Therefore, some models for the automatic retrieval of microblogs froman exterior corpus have been proposed. However, these approaches may fail in considering microblog-specific features. To alleviate this issue, we propose a methodology that constructs a simulated microblogging corpus rather than directly building a model from the exterior corpus. The performance of our model is better since the microblog-special knowledge of the microblogging corpus is used in the end by the retrieval model. Experimental results on real-world microblogs demonstrate the superiority of our technique compared to the previous approaches.
Cite
Text
Tu et al. "Improving Microblog Retrieval from Exterior Corpus by Automatically Constructing Microblogging Corpus." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9716Markdown
[Tu et al. "Improving Microblog Retrieval from Exterior Corpus by Automatically Constructing Microblogging Corpus." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/tu2015aaai-improving/) doi:10.1609/AAAI.V29I1.9716BibTeX
@inproceedings{tu2015aaai-improving,
title = {{Improving Microblog Retrieval from Exterior Corpus by Automatically Constructing Microblogging Corpus}},
author = {Tu, Wenting and Cheung, David Wai-Lok and Mamoulis, Nikos},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2015},
pages = {4212-4213},
doi = {10.1609/AAAI.V29I1.9716},
url = {https://mlanthology.org/aaai/2015/tu2015aaai-improving/}
}