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Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering
Published on Oct 08, 20073444 Views
We present a novel approach to the growing neural gas (GNG) based clustering of the high-dimensional text data. We enhance our Contextual GNG models (proposed previously to shift the majority of cal
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Chapter list
Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering00:00
Outline - BEATCA Overview00:27
BEATCA Overview01:09
Outline - Contextual Approach02:27
Contextual Approach: Vector Space Model02:33
Contextual Approach: Contextual Maps04:38
Contextual Approach: Contextual Term Weights05:50
Contextual Approach: Advantages07:47
Outline - Histograms08:48
Histograms: Concept Overview09:28
Histograms: Contextual Term/Document Importance11:08
Histograms: Some Applications11:49
Outline - Experimental Results12:36
Experimental Results: Experimental Setting pt 112:48
Experimental Results: Experimental Setting pt 213:12
Experimental Results: Reclassification Measure13:33
Experimental Results: Reclassification Results pt 114:08
Experimental Results: Reclassification Results pt 215:18
Experimental Results: Reclassification Results pt 315:44
Experimental Results: Reclassification Results pt 417:21
Outline - Conclusions17:45
Conclusions: Summary17:47
Conclusions: Future Research18:47