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Episodic Memory for Ubiquitous Multimedia Contents Management System

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New Trends in Applied Artificial Intelligence (IEA/AIE 2007)

Abstract

Recently, mobile devices are regarded as a content storage with their functions such as camera, camcorder, and music player. It creates massive new data and downloads contents from desktop or wireless internet. Because of the massive size of digital contents in the mobile devices, user feels difficulty to recall or find information from the personal storage. If it is possible to organize the storage in a style of human-memory management, it could reduce user’s effort in contents management. Based on the evidence that human memory is organized as an episodic-style, we propose a KeyGraph-based reorganization method of mobile device storage for better accessibility to the data. It can help user not only find useful information from the storage but also expand his/her memory by adding user’s contexts such as location, SMS, call, and device status. User can recall his/her memory from the contents and contexts. KeyGraph finds rare but relevant events that can be used as a memory landmark in the episodic memory. Using artificially generated logs from a pre-defined scenario, the proposed method is tested and analyzed to check the possibility.

This research was supported in part by MIC, Korea under ITRC IITA-2006-(C1090-0603-0046).

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Hiroshi G. Okuno Moonis Ali

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Kim, KJ., Jung, MC., Cho, SB. (2007). Episodic Memory for Ubiquitous Multimedia Contents Management System. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_79

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  • DOI: https://doi.org/10.1007/978-3-540-73325-6_79

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73322-5

  • Online ISBN: 978-3-540-73325-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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