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Mining Intention-Related Products on Online Q&A Community

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Abstract

User generated content on social media has attracted much attention from service/product providers, as it contains plenty of potential commercial opportunities. However, previous work mainly focuses on user consumption intention (CI) identification, and little effort has been spent to mine intention-related products. In this paper, focusing on the Baby & Child Care domain, we propose a novel approach to mine intention-related products on online question and answer (Q&A) community. Making use of the question-answering pairs as data source, we first automatically extract candidate products based on dependency parser. And then by means of the collocation extraction model, we identify the real intention-related products from the candidate set. The experimental results on our carefully constructed evaluation dataset show that our approach achieves better performance than two natural baseline methods.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Jun-Wen Duan, Yi-Heng Chen, Ting Liu & Xiao Ding

Authors
  1. Jun-Wen Duan
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  2. Yi-Heng Chen
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  3. Ting Liu
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  4. Xiao Ding
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Correspondence to Ting Liu.

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Duan, JW., Chen, YH., Liu, T. et al. Mining Intention-Related Products on Online Q&A Community. J. Comput. Sci. Technol. 30, 1054–1062 (2015). https://doi.org/10.1007/s11390-015-1581-7

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  • DOI: https://doi.org/10.1007/s11390-015-1581-7

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