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

Neil Y. Yen, James J. Park, Qun Jin, Timothy K. Shih

研究成果: 雜誌貢獻期刊論文同行評審

4 引文 斯高帕斯(Scopus)


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 usergenerated contents, an intelligent state machine, as a hybridization of graph model (Document Graph) and petrinet model (Document Sensitive Petri-Net), is proposed. It is utilized to clarify the vague usage scenario between usergenerated 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.

頁(從 - 到)1731-1739
期刊Personal and Ubiquitous Computing
出版狀態已出版 - 12月 2013


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