2026-09-19T05:00:43Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/421232022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Larry Rudolph.
Yan, Emily Z
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2008-09-03T14:39:27Z
2008-09-03T14:39:27Z
2006
2006
http://hdl.handle.net/1721.1/42123
227037789
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 53-54).
Much information can be obtained from knowing what tasks the user does on his or her cell phone. This paper describes GuiDE, an automated user-activity recognition system on the mobile phone. GuiDE's unique approach to activity recognition exploits GUI screenshots taken as the individual interacts with their cell phone. These screenshots are aggregated into a graph to help probabilistically determine whether or not a set of screenshots can be considered a user-level activity. A frequency count of different sets of screenshots is also kept to act as a sanity check against the probabilistic result. GuiDE is just a partial step towards a much more powerful tool that can correlate GUI information with other services to provide a better understanding of user activity.
by Emily Z. Yan.
M.Eng.
54 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
A mobile phone GuiDE : a GUI Decoder and Enricher
GUI Decoder and Enricher
Thesis
application/pdf
false
Publication
unknown
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<Abstract>Much information can be obtained from knowing what tasks the user does on his or her cell phone. This paper describes GuiDE, an automated user-activity recognition system on the mobile phone. GuiDE's unique approach to activity recognition exploits GUI screenshots taken as the individual interacts with their cell phone. These screenshots are aggregated into a graph to help probabilistically determine whether or not a set of screenshots can be considered a user-level activity. A frequency count of different sets of screenshots is also kept to act as a sanity check against the probabilistic result. GuiDE is just a partial step towards a much more powerful tool that can correlate GUI information with other services to provide a better understanding of user activity.</Abstract>
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