ISSN 1000-1239 CN 11-1777/TP

Special Issue: 2016数据融合与知识融合专题

### Short Text Understanding: A Survey

Wang Zhongyuan1,2, Cheng Jianpeng2,3, Wang Haixun4, Wen Jirong1

1. 1(School of Information, Renmin University of China, Beijing 100872); 2(Microsoft Research Asia, Beijing 100080); 2(Department of Computer Science, Oxford University, OXford, UK OX1 3QD); 4(Facebook, Menlo Park, CA, USA 94025)
• Online:2016-02-01

Abstract: 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.

CLC Number:
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