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27 February 2008 Personalized summarization using user preference for m-learning
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Proceedings Volume 6821, Multimedia on Mobile Devices 2008; 68210P (2008)
Event: Electronic Imaging, 2008, San Jose, California, United States
As the Internet and multimedia technology is becoming advanced, the number of digital multimedia contents is also becoming abundant in learning area. In order to facilitate the access of digital knowledge and to meet the need of a lifelong learning, e-learning could be the helpful alternative way to the conventional learning paradigms. E-learning is known as a unifying term to express online, web-based and technology-delivered learning. Mobile-learning (m-learning) is defined as e-learning through mobile devices using wireless transmission. In a survey, more than half of the people remarked that the re-consumption was one of the convenient features in e-learning. However, it is not easy to find user's preferred segmentation from a full version of lengthy e-learning content. Especially in m-learning, a content-summarization method is strongly required because mobile devices are limited to low processing power and battery capacity. In this paper, we propose a new user preference model for re-consumption to construct personalized summarization for re-consumption. The user preference for re-consumption is modeled based on user actions with statistical model. Based on the user preference model for re-consumption with personalized user actions, our method discriminates preferred parts over the entire content. Experimental results demonstrated successful personalized summarization.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sihyoung Lee, Seungji Yang, Yong Man Ro, and Hyoung Joong Kim "Personalized summarization using user preference for m-learning", Proc. SPIE 6821, Multimedia on Mobile Devices 2008, 68210P (27 February 2008);


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