@article{b748e232d5c445d1933f5539adbe92cf,
title = "Guiding supervised topic modeling for content based tag recommendation",
abstract = "Automatically recommending suitable tags for online content is a necessary task for better information organization and retrieval. In this article, we propose a generative model SIMWORD for the tag recommendation problem on textual content. The key observation of our model is that the tags and their relevant/similar words may have appeared in the corresponding content. In particular, we first empirically verify this observation in real data sets, and then design a supervised topic model which is guided by the above observation for tag recommendation. Experimental evaluations demonstrate that the proposed method outperforms several existing methods in terms of recommendation accuracy.",
keywords = "Generative model, Relevant words, Similar words, Supervised topic modeling, Tag recommendation",
author = "Yong Wu and Shengqu Xi and Yuan Yao and Feng Xu and Hanghang Tong and Jian Lu",
note = "Funding Information: This work is supported by the National Key R&D Program of China (No. 2016YFB1000802), the National Natural Science Foundation of China (No. 61690204, 61672274, 61702252), and the Collaborative Innovation Center of Novel Software Technology and Industrialization. Hanghang Tong is partially supported by NSF ( IIS-1651203 , IIS-1715385, CNS-1629888 and IIS-1743040 ), DTRA ( HDTRA1-16-0017 ), ARO ( W911NF-16-1-0168 ), and gifts from Huawei and Baidu. Funding Information: This work is supported by the National Key R&D Program of China (No. 2016YFB1000802), the National Natural Science Foundation of China (No. 61690204, 61672274, 61702252), and the Collaborative Innovation Center of Novel Software Technology and Industrialization. Hanghang Tong is partially supported by NSF (IIS-1651203, IIS-1715385, CNS-1629888 and IIS-1743040), DTRA (HDTRA1-16-0017), ARO (W911NF-16-1-0168), and gifts from Huawei and Baidu. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V.",
year = "2018",
month = nov,
day = "7",
doi = "10.1016/j.neucom.2018.07.011",
language = "English (US)",
volume = "314",
pages = "479--489",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",
}