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» Using Data Mining to Estimate Missing Sensor Data
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IRI
2005
IEEE
15 years 3 months ago
Handling missing values via decomposition of the conditioned set
In this paper, a framework for replacing missing values in a database is proposed since a real-world database is seldom complete. Good data quality in a database can directly impr...
Mei-Ling Shyu, Indika Kuruppu-Appuhamilage, Shu-Ch...
ICDCS
2008
IEEE
15 years 3 months ago
Data Estimation in Sensor Networks Using Physical and Statistical Methodologies
Wireless Sensor Networks (WSNs) are employed in many applications in order to collect data. One key challenge is to minimize energy consumption to prolong network lifetime. A sche...
Yingshu Li, Chunyu Ai, Wiwek P. Deshmukh, Yiwei Wu
89
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ICAI
2010
14 years 7 months ago
Using Sensor Sequences for Activity Recognition by Mining and Multi-Class Adaboost
- In this paper, we present an activity recognition system using sensor sequence information generated from many binary on-off state sensors. When many sensors are deployed the num...
Md. Kamrul Hasan, Sungyoung Lee, Young-Koo Lee
ICDM
2006
IEEE
169views Data Mining» more  ICDM 2006»
15 years 3 months ago
Privacy-Preserving Data Imputation
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...
Geetha Jagannathan, Rebecca N. Wright
BMCBI
2008
190views more  BMCBI 2008»
14 years 9 months ago
Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes
Background: Gene expression data frequently contain missing values, however, most downstream analyses for microarray experiments require complete data. In the literature many meth...
Guy N. Brock, John R. Shaffer, Richard E. Blakesle...