@inproceedings{b019bfc1772849459e5f0970dd52fe89,
title = "A short text topic discovery method for social network",
abstract = "Short text theme discovery is the discovery of hot topic from short text data in mass. As the micro-blog social network has distinct characteristics of the network language, new words emerge in an endless stream. This paper presents an improved method for short text theme found, First, based on HMM model discovered new words to the text, new words are added to the user dictionary, and then we use discovery results of new words to build LDA model, finally, get the document clustering-topic distribution. The experimental results show that this method can effectively enhance the comprehensiveness and accuracy of the topic discovery and is more suitable for theme mining under social network environment.",
keywords = "Hot Topic Detection, Micro-blog, New Word Discovery, Social Network",
author = "Jia Liu and Qinglin Wang and Yu Liu and Yuan Li",
note = "Publisher Copyright: {\textcopyright} 2014 TCCT, CAA.; Proceedings of the 33rd Chinese Control Conference, CCC 2014 ; Conference date: 28-07-2014 Through 30-07-2014",
year = "2014",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2014.6896676",
language = "English",
series = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
publisher = "IEEE Computer Society",
pages = "512--516",
editor = "Shengyuan Xu and Qianchuan Zhao",
booktitle = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
address = "United States",
}