IoT Data Quality

Author:

Song Shaoxu1,Zhang Aoqian2

Affiliation:

1. Tsinghua University, Beijing, China

2. University of Waterloo, Waterloo, Canada

Publisher

ACM

Reference47 articles.

1. Temporal rules discovery for web data cleaning

2. Reza Asadi and Amelia Regan. 2019. A convolution recurrent autoencoder for spatio-temporal missing data imputation. CoRR Vol. abs/1904.12413 (2019). Reza Asadi and Amelia Regan. 2019. A convolution recurrent autoencoder for spatio-temporal missing data imputation. CoRR Vol. abs/1904.12413 (2019).

3. Asif Iqbal Baba Manfred Jaeger Hua Lu Torben Bach Pedersen Wei-Shinn Ku and Xike Xie. 2016. Learning-Based Cleansing for Indoor RFID Data. In SIGMOD. 925--936. Asif Iqbal Baba Manfred Jaeger Hua Lu Torben Bach Pedersen Wei-Shinn Ku and Xike Xie. 2016. Learning-Based Cleansing for Indoor RFID Data. In SIGMOD. 925--936.

4. Laure Berti-É quille Tamraparni Dasu and Divesh Srivastava. 2011. Discovery of complex glitch patterns: A novel approach to Quantitative Data Cleaning. In ICDE. 733--744. Laure Berti-É quille Tamraparni Dasu and Divesh Srivastava. 2011. Discovery of complex glitch patterns: A novel approach to Quantitative Data Cleaning. In ICDE. 733--744.

5. Facets

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