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LIFEREC: A Framework for Recommending Users from Past Life Experiences.

Author(s)
Mohsin Ali Memon Department of Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
SANIA BHATTI Department of Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
SHAHZAD NIZAMINI Department of Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
Naeem Ahmed Mahoto Department of Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
FARIDA MEMON Department of Electronics Engineering, Mehran University of Engineering & Technology, Jamshoro,
Abstract
Life logging has been an eminent topic of concern in recent years with many researchers focusing on capturing daily life activities of human. With the proliferation of IoT (Internet of Things) domain, the devices are now able to record human interaction for longer periods as well as transfer this data easily to other computing devices or cloud storage. This article proposes a novel framework named as LIFEREC which acquires information from IoT aware devices and sensors. It maintains activity profiles of various activities performed by the users in their daily lives. Furthermore, the framework provides recommendations when requested by an individual while taking into account the past life history and current context. Recent research on digitizing human life is quite efficient in amassing enormous data but futile in offering assistance for prospect decisions in life. The data gathered by the lifelog devices may be of a great help in taking decisions. The proposed system gives a new direction to existing mechanisms of providing recommendations by exploiting the current context and the past experiences of human life. The recommendations provided by our proposed system may be very helpful while performing those activities which have already been experienced in the past.
Publication Details
Page(s) 661-672
DOI DOI not available
Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 36, Issue: 3, Year: 2017

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