文章基本信息

标题：Short Text Classification: A Survey
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作者：Song, Ge ; Ye, Yunming ; Du, Xiaolin 等
期刊名称：Journal of Multimedia
印刷版ISSN：1796-2048
出版年度：2014
卷号：9
期号：5
页码：635-643
DOI：10.4304/jmm.9.5.635-643
语种：English
出版社：Academy Publisher
摘要：With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification
关键词：Short Text;Text Classification;Feature Selection;Semantic Analysis;Integrated Learning;Semi-Supervised Learning