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    Wang Zhongyuan, Cheng Jianpeng, Wang Haixun, Wen Jirong. Short Text Understanding: A Survey[J]. Journal of Computer Research and Development, 2016, 53(2): 262-269. DOI: 10.7544/issn1000-1239.2016.20150742
    Citation: Wang Zhongyuan, Cheng Jianpeng, Wang Haixun, Wen Jirong. Short Text Understanding: A Survey[J]. Journal of Computer Research and Development, 2016, 53(2): 262-269. DOI: 10.7544/issn1000-1239.2016.20150742

    Short Text Understanding: A Survey

    • Short text understanding is an important but challenging task relevant for machine intelligence. The task can potentially benefit various online applications, such as search engines, automatic question-answering, online advertising and recommendation systems. In all these applications, the necessary first step is to transform an input text into a machine-interpretable representation, namely to “understand” the short text. To achieve this goal, various approaches have been proposed to leverage external knowledge sources as a complement to the inadequate contextual information accompanying short texts. This survey reviews current progress in short text understanding with a focus on the vector based approaches, which aim to derive the vectorial encoding for a short text. We also explore a few potential research topics in the field of short text understanding.
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