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User-centered innovative technology analysis and prediction application in mobile environment

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Abstract

Business intelligence is a critical in defining the strategy and roadmap of organizations. However, business intelligence covers too much wide coverage to consider all of fields such as data analytics, text mining, predictive analytics, and so on. Among these fields, the most important is information analysis and prediction. Therefore, we suggest a business intelligence application based on the adaptive recognition of user intention and usage patterns in the mobile environment. This application is named InSciTe Adaptive and is based on text mining and semantic web technologies. It supports technology-focused analysis and predictions, such as technology trends analysis, element technology analysis, and convergence technology discovery, as well as adaptive recognition of the user’s intention by using semi-automatic user modeling processes. Through adaptive user modeling, this application can provide a more dynamic service flow and more up-to-date analysis results based on the user’s intention, compared to existing applications, which provide static analysis results and service flow.

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Authors and Affiliations

  1. Department of Computer Intelligence Research, Information/Software Research Center, Korea Institute of Science and Technology Information, 52-11, Eoeun-dong, Yuseong-gu, Daejeon, South Korea

    Jinhyung Kim, Do-Heon Jeong & Hanmin Jung

  2. Department of Industrial Security, Kyunggi University, 154-42, Gwanggyosan-ro, YoungTong-gu, Suwon, South Korea

    DongHwi Lee

Authors
  1. Jinhyung Kim
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  2. Do-Heon Jeong
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  3. DongHwi Lee
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  4. Hanmin Jung
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Corresponding authors

Correspondence to Jinhyung Kim or Do-Heon Jeong.

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Kim, J., Jeong, DH., Lee, D. et al. User-centered innovative technology analysis and prediction application in mobile environment. Multimed Tools Appl 74, 8761–8779 (2015). https://doi.org/10.1007/s11042-013-1486-9

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