Abstract
Online mining in large sensor networks just starts to attract interest. Finding patterns in such an environment is both compelling and challenging. The goal of this position paper is to understand the challenges and to identify the research problems in online mining for sensor networks. As an initial step, we identify the following three problems to work on: (1) sensor data irregularities detection; (2) sensor data clustering; and (3) sensory attribute correlations discovery. We also outline our preliminary proposal of solutions to these problems. © IFIP International Federation for Information Processing 2004.
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CITATION STYLE
Xiuli, M., Yang, D., Tang, S., Luo, Q., Zhang, D., & Li, S. (2004). Online mining in sensor networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3222, 544–550. https://doi.org/10.1007/978-3-540-30141-7_81
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