Abstract. Analyzing clustering structures in data streams can provide critical information for making decision in real- time. In this paper, we present a ...
Abstract. Analyzing clustering structures in data streams can provide critical information for making decision in real- time. Most research has been focused ...
In this paper, we present a framework for detecting the change of critical clustering structure in categorical data streams. The framework consists of the ...
Clustering data streams can provide critical infor- mation for making decision in real-time. We argue that detecting the change of clustering structure in.
Analyzing clustering structures in data streams can provide critical information for making decision in real- time. In this paper, we present a framework ...
[PDF] Detecting the Change of Clustering Structure in Categorical ...
www.semanticscholar.org › paper
HE-Tree: a framework for detecting changes in clustering structure for categorical data streams · “Best K”: critical clustering structures in categorical ...
In this paper, we present a framework for detecting changes of clustering structure in categorical data streams. The change of clustering structure is detected ...
Analyzing clustering structures in data streams can provide critical information for real-time decision making. Most research in this area has focused on ...
The HE-Tree can efficiently summarize the entropy property of a categorical data stream and allow us to draw precise clustering information from the data stream ...
People also ask
How to do cluster analysis on categorical data?
Why is it difficult to handle categorical data for clustering?
What distance metrics to use when clustering with categorical data?
Does hierarchical clustering work with categorical data?
Bibliographic details on Detecting the Change of Clustering Structure in Categorical Data Streams.