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Improving hierarchical document cluster labels through candidate term selection
(2012-09-03)
One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for ...
Selecting candidate labels for hierarchical document clusters using association rules
(2010-12-16)
One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for ...
Improving hierarchical document cluster labels through candidate term selection
(2012-09-03)
One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for ...
Selecting candidate labels for hierarchical document clusters using association rules
(2010-12-16)
One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for ...
A GH-SOM optimization with SOM labelling and dunn index
(Scopus, 2011)
Clustering is an unsupervised classification method that divides a data set in groups, where the elements of a group have similar characteristics to each other. A well-known clustering method is the Growing Hierarchical ...
Hierarchical density estimates for data clustering, visualization, and outlier detection
(ACMNew York, 2015-07)
An integrated framework for density-based cluster analysis, outlier detection, and data visualization is introduced in this article. The main module consists of an algorithm to compute hierarchical estimates of the level ...
Incremental Hierarchical Clustering driven Automatic Annotations for Unifying IoT Streaming Data
In the Internet of Things (IoT), Cyber-Physical Systems (CPS), and sensor technologies huge and variety of streaming sensor data is generated. The unification of streaming sensor data is a challenging problem. Moreover, ...
Hierarchical clustering and stochastic distance for indirect semi-supervised remote sensing image classification
(Springer, 2019-03-01)
Usually, image classification methods have supervised or unsupervised learning paradigms. While unsupervised methods do not need training data, the meanings behind the classified elements are not explicitly know. Conversely, ...