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Extended search method based on a semantic hashtag graph combining social and conceptual information

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Abstract

Searching for microblog short text by their meaning is a challenging task because of the semantic sparsity of the information in social networks. The extended search approaches are commonly accepted which facilitate short text understanding and search by enriching the short text. However, they only analyze the literal semantics of short text, and the unique social characteristics of social network which also contain semantic information are not utilized well. To better capture the rich semantics in microblog short text, we propose a new microblog short text extended search method based on a semantic hashtag graph by combining social and conceptual information, which enriches each short text by concepts and associated hashtags to represent whole semantic features. Considering the microblog context, we introduce concepts through Wikipedia, as well as semantic consistency of hashtags. Specifically, for conceptual semantics, we propose a conceptual analysis method which merges explicit and implicit information in Wikipedia. For social semantics in hashtags, a semantic hashtag graph which combines social and conceptual information is put forward to generate semantic associated hashtags. We conduct experiments and the results show that our method is obviously better than the other existing state-of-the-art approaches in semantic understanding and search of short text.

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Notes

  1. http://lucene.apache.org

  2. https://en.wikipedia.org/wiki/Wikipedia:Database_download

  3. http://medialab.di.unipi.it/wiki/Wikipedia_Extractor

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) under Grant (No.61320106006, No.61532006, No.61772083, No. 61502042).

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Authors and Affiliations

  1. Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

    Wanqiu Cui, Junping Du, Feifei Kou, Meiyu Liang, Zhe Xue & Nan Zhou

  2. School of Information, Renmin University of China, Beijing, China

    Dawei Wang

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  1. Wanqiu Cui
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Correspondence to Junping Du.

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This article belongs to the Topical Collection: Special Issue on Web and Big Data

Guest Editors: Junjie Yao, Bin Cui, Christian S. Jensen, and Zhe Zhao

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Cui, W., Du, J., Wang, D. et al. Extended search method based on a semantic hashtag graph combining social and conceptual information. World Wide Web 22, 2589–2610 (2019). https://doi.org/10.1007/s11280-018-0584-z

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