Abstract
Microblog is a social platform with huge user community and mass data. We propose a semantic recommendation mechanism based on sentiment analysis for microblog. Firstly, the keywords and sensibility words in this mechanism are extracted by natural language processing including segmentation, lexical analysis and strategy selection. Then, we query the background knowledge base based on linked open data (LOD) with the basic information of users. The experiment result shows that the accuracy of recommendation is within the range of 70% -89% with sentiment analysis and semantic query. Compared with traditional recommendation method, this method can satisfy users’ requirement greatly.
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Foundation item: Supported by the National Natural Science Foundation of China(60803160 and 61272110), the Key Projects of National Social Science Foundation of China(11&ZD189), the Natural Science Foundation of Hubei Province(2013CFB334), the Natural Science Foundation of Educational Agency of Hubei Province(Q20101110), the State Key Lab of Software Engineering Open Foundation of Wuhan University (SKLSE2012-09-07), the Teaching Research Project of Hubei Province (2011s005) and the Wuhan Key Technology Support Program(2013010602010216)
Biography: TIAN Pingfang, female, Master, Associate professor, research direction: artificial intelligence, semantic Web.
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Tian, P., Zhu, Z., Xiong, L. et al. A recommendation mechanism for web publishing based on sentiment analysis of microblog. Wuhan Univ. J. Nat. Sci. 20, 146–152 (2015). https://doi.org/10.1007/s11859-015-1073-1
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DOI: https://doi.org/10.1007/s11859-015-1073-1