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Skip to Search Results- 14Sander, Joerg (Computing Science)
- 2Rafiei, Davood (Computing Science)
- 1Nascimento, Mario (Computing Science)
- 1Nascimento, Mario A. (Computing Science)
- 1Parsons, Ian (Computing Science)
- 1Rafiei, Davood(Computing Science)
- 2Clustering
- 1Anomaly Detection
- 1Anomaly detection
- 1Attribute-value pairs
- 1Clustering parameter
- 1Co-location pattern
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Spring 2015
Cluster analysis plays a very important role for understanding various phenomena about data without any prior knowledge. However, hierarchical clustering algorithms, which are widely used for its representation of data, are computationally expensive. Recently large datasets are prevalent in many...
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Spring 2014
Spatial interaction pattern mining is the process of discovering patterns that occur due to the interaction of Boolean features from a spatial domain. A positive interaction of a subset of features generates a co-location pattern, whereas a negative interaction of a subset of features generates a...
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Fall 2020
The Web contains an enormous amount of structured data in the form of web tables, and there is a great value in retrieving this data and harnessing it for decision making and gain more insights. Finding the right data on the Web and integrating it with the existing data within an organization can...
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Fall 2013
Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from the rest of the subsequences. Discovery of time series discords has been applied to several diverse domains including space shuttle telemetry, industry,...