SearchSkip to Search Results
- 2Sensor networks
- 1Clustering algorithms
- 1Communication Networks
- 1Distributed algorithms
- 1Distributed data management
Finding non-Redundant, Statistically Significant Regions in High Dimensional Data: a Novel Approach to Projected and Subspace ClusteringDownload
Technical report TR08-03. Projected and subspace clustering algorithms search for clusters of objects in subsets of attributes. Projected clustering computes several disjoint clusters, plus outliers, so that each cluster exists in its own subset of attributes. Subspace clustering enumerates...
Technical report TR04-24. This thesis studies the problem of effectively finding related pages on the Web, where given the URL of a page, one wants to find other pages that are on the same topic. This is a both simple and natural way of searching for resources without being forced to formulate a...
Technical report TR05-23. Wireless sensor networks are made of autonomous devices that are able to collect information, store it, process it and share it with other devices. Such framework can be used to efficiently query spatiotemporal data, e.g., for monitoring humidity and temperature levels...
Technical report TR06-24. Wireless sensor networks have received much attention recently. Given their autonomy, flexibility and large range of functionality, they can be used as an effective and discrete means for monitoring data in many domains. Typically the network autonomy implies a limited...
Technical report TR08-09. Many clustering algorithms in particular hierarchical clustering algorithms do not scale-up well for large data-sets especially when using an expensive distance function. In this paper, we propose a novel approach to perform approximate clustering with high accuracy....