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» Computable social patterns from sparse sensor data
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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 7 days ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
VLDB
2004
ACM
100views Database» more  VLDB 2004»
15 years 3 months ago
Resilient Rights Protection for Sensor Streams
Today’s world of increasingly dynamic computing environments naturally results in more and more data being available as fast streams. Applications such as stock market analysis,...
Radu Sion, Mikhail J. Atallah, Sunil Prabhakar
MOBIHOC
2001
ACM
15 years 9 months ago
Highly-resilient, energy-efficient multipath routing in wireless sensor networks
Previously proposed sensor network data dissemination schemes require periodic low-rate flooding of data in order to allow recovery from failure. We consider constructing two kind...
Deepak Ganesan, Ramesh Govindan, Scott Shenker, De...
UM
2009
Springer
15 years 4 months ago
Predicting Customer Models Using Behavior-Based Features in Shops
Abstract. Recent sensor technologies have enabled the capture of users’ behavior data. Given the large amount of data currently available from sensor-equipped environments, it is...
Junichiro Mori, Yutaka Matsuo, Hitoshi Koshiba, Ke...
SIGMOD
2003
ACM
121views Database» more  SIGMOD 2003»
15 years 10 months ago
An environmental sensor network to determine drinking water quality and security
Finding patterns in large, real, spatio/temporal data continues to attract high interest (e.g., sales of products over space and time, patterns in mobile phone users; sensor netwo...
Anastassia Ailamaki, Christos Faloutsos, Paul S. F...