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Exploring External Knowledge Base for Personalized Search in Collaborative Tagging Systems

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Collaborate Computing: Networking, Applications and Worksharing (CollaborateCom 2016)

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Abstract

Alongside the enormous volume of user-generated content posted to World Wide Web, there exists a thriving demand for search personalization services, especially those utilizing collaborative tagging data. To provide personalized services, a user model is usually required. We address the setting adopted by the majority of previous work, where a user model consists solely of the user’s past information. We construct an augmented user model from a number of tags and documents. These resources are further processed according to the user’s past information by exploring external knowledge base. A novel generative model is proposed for user model generation. This model leverages recent advances in neural language models such as Word Embeddings with latent semantic models such as Latent Dirichlet Allocation. We further present a new query expansion method to facilitate the desired personalized retrieval. Experiments conducted by utilizing real-world collaborative tagging data show that the methods proposed in the current paper outperform several non-personalized methods as well as existing personalized search methods by utilizing user models solely constructed from usage histories.

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Notes

  1. 1.

    http://www.delicious.com/.

  2. 2.

    http://www.bibsonomy.org.

  3. 3.

    http://www.wikipedia.org.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (61300129, 61572187 and 61272063), Scientific Research Fund of Hunan Provincial Education Department of China (16K030), Hunan Provincial Innovation Foundation For Postgraduate (CX2016B575). This research was also supported by the ADAPT Centre for Digital Content Technology, which is funded under the Science Foundation Ireland Research Centres Programme (13/RC/2106) and is co-funded under the European Regional Development Fund.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Dong Zhou, Xuan Wu, Wenyu Zhao & Jianxun Liu

  2. ADAPT Centre, Knowledge and Date Engineering Group, School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland

    Séamus Lawless

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  1. Dong Zhou
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  2. Xuan Wu
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  3. Wenyu Zhao
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  4. Séamus Lawless
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  5. Jianxun Liu
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Correspondence to Dong Zhou .

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Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Ao Zhou

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhou, D., Wu, X., Zhao, W., Lawless, S., Liu, J. (2017). Exploring External Knowledge Base for Personalized Search in Collaborative Tagging Systems. In: Wang, S., Zhou, A. (eds) Collaborate Computing: Networking, Applications and Worksharing. CollaborateCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 201. Springer, Cham. https://doi.org/10.1007/978-3-319-59288-6_37

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  • DOI: https://doi.org/10.1007/978-3-319-59288-6_37

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-59288-6

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