@inproceedings{5d57a404e6ba4618be206a1e4131b160,
title = "O-hetm: An online hierarchical entity topic model for news streams",
abstract = "Nowadays, with the development of the Internet, large amount of continuous streaming news has become overwhelming to the public. Constructing a dynamic topic hierarchy which organizes the news articles according tomulti-grain topics can enable the users to catch whatever they are interested in as soon as possible. However, it is nontrivial due to the streaming and time-sensitive characteristics of news data. In this paper, to address the challenges, we propose a Hierarchical Entity Topic Model (HETM)which considers the timeliness of news data and the importance of named entities in conveying information of who/when/where in news articles. In addition, we propose onlineHETM(o-HETM) by presenting a fast online inference algorithm for HETM to adapt it to streaming news. For better understanding of topics, we extract key sentences for each topic to form a summary. Extensive experimental results demonstrate that our model HETM significantly improves the topic quality and time efficiency, compared to state-of-the-art method HLDA (Hierarchical Latent Dirichlet Allocation). In addition, our proposed o-HETM with an online inference algorithm further greatly improves the time efficiency and thus can be applicable to the streaming news.",
keywords = "Hierarchical entity topic model, News streams, Online inference, Topic hierarchy",
author = "Linmei Hu and Juanzi Li and Jing Zhang and Chao Shao",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015 ; Conference date: 19-05-2015 Through 22-05-2015",
year = "2015",
doi = "10.1007/978-3-319-18038-0\_54",
language = "English",
isbn = "9783319180373",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "696--707",
editor = "Tru Cao and Ee-Peng Lim and Zhi-Hua Zhou and Tu-Bao Ho and David Cheung and Hiroshi Motoda and Hiroshi Motoda",
booktitle = "Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference, PAKDD 2015, Proceedings",
address = "Germany",
}