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Modeling user-generated contents: an intelligent state machine for user-centric search support

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Abstract

Researchers tend to agree that an increasing quantity of data has caused the complexity and difficulty for information discovery, management, and reuse. An essential factor relates to the increasing channels (i.e., Internet, social media, etc.) for information sharing. Finding information, especially those meaningful or useful one, that meets ultimate goal (or task) of user becomes harder then it is used to be. In this research, issues concerning the use of user-generated contents for individual search support are investigated. In order to make efficient use of user-generated contents, an intelligent state machine, as a hybridization of graph model (Document Graph) and petri-net model (Document Sensitive Petri-Net), is proposed. It is utilized to clarify the vague usage scenario between user-generated contents, such as discussions, posts, etc., and to identify correlations and experiences within them. As a practical contribution, an interactive search algorithm that generates potential solutions for individual is implemented. The feasibility of this research is demonstrated by a series of experiments and empirical studies with around 350,000 user-generated contents (i.e., documents) collected from the Internet and 200 users.

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Acknowledgments

This research was supported by the RONPAKU Program of JSPS (Japan Society for the Promotion of Science), Japan, from April 2010 to March 2012. The work was also partly supported by the National Science Council of Taiwan and 2010-2012 Waseda University Advanced Research Center for Human Sciences Project.

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Authors and Affiliations

  1. School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Japan

    Neil Y. Yen

  2. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea

    James J. (Jong Hyuk) Park

  3. Department of Human Informatics and Cognitive Sciences, Waseda University, Tokyo, Japan

    Qun Jin

  4. Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan

    Timothy K. Shih

Authors
  1. Neil Y. Yen
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  2. James J. (Jong Hyuk) Park
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  3. Qun Jin
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  4. Timothy K. Shih
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Corresponding author

Correspondence to James J. (Jong Hyuk) Park.

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Yen, N.Y., (Jong Hyuk) Park, J.J., Jin, Q. et al. Modeling user-generated contents: an intelligent state machine for user-centric search support. Pers Ubiquit Comput 17, 1731–1739 (2013). https://doi.org/10.1007/s00779-012-0607-1

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  • DOI: https://doi.org/10.1007/s00779-012-0607-1

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