|
|
|
|
LEADER |
02547 am a22003133u 4500 |
001 |
101031 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Feldman, Dan
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
|e contributor
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
|e contributor
|
100 |
1 |
0 |
|a Feldman, Dan
|e contributor
|
100 |
1 |
0 |
|a Sugaya, Andrew
|e contributor
|
100 |
1 |
0 |
|a Sung, Cynthia Rueyi
|e contributor
|
100 |
1 |
0 |
|a Rus, Daniela L.
|e contributor
|
700 |
1 |
0 |
|a Sugaya, Andrew
|e author
|
700 |
1 |
0 |
|a Sung, Cynthia Rueyi
|e author
|
700 |
1 |
0 |
|a Rus, Daniela L.
|e author
|
245 |
0 |
0 |
|a iDiary: from GPS signals to a text-searchable diary
|
260 |
|
|
|b Association for Computing Machinery (ACM),
|c 2016-01-29T00:58:54Z.
|
856 |
|
|
|z Get fulltext
|u http://hdl.handle.net/1721.1/101031
|
520 |
|
|
|a This paper describes a system that takes as input GPS data streams generated by users' phones and creates a searchable database of locations and activities. The system is called iDiary and turns large GPS signals collected from smartphones into textual descriptions of the trajectories. The system features a user interface similar to Google Search that allows users to type text queries on their activities (e.g., "Where did I buy books?") and receive textual answers based on their GPS signals. iDiary uses novel algorithms for semantic compression (known as coresets) and trajectory clustering of massive GPS signals in parallel to compute the critical locations of a user. Using an external database, we then map these locations to textual descriptions and activities so that we can apply text mining techniques on the resulting data (e.g. LSA or transportation mode recognition). We provide experimental results for both the system and algorithms and compare them to existing commercial and academic state-of-the-art. This is the first GPS system that enables text-searchable activities from GPS data.
|
520 |
|
|
|a United States. Office of Naval Research (Grant ONR-MURI Award N00014-12-1-1000)
|
520 |
|
|
|a Hon Hai/Foxconn International Holdings Ltd.
|
520 |
|
|
|a Singapore-MIT Alliance for Research and Technology Center
|
520 |
|
|
|a Singapore. National Research Foundation
|
520 |
|
|
|a United States. Dept. of Defense. National Defense Science & Engineering Graduate Fellowship Program
|
546 |
|
|
|a en_US
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems (SenSys '13)
|