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13 Clustering - exercise

Text Mining Course: Clustering

- What groups of documents are in the data?
- Compute pairwise cosine distances
- Apply hierarchical clustering
- View dendrogram to find out the number of clusters (k)
- Assign k clusters
- Apply k-Medoids with k as number of clusters
- Select documents of one cluster in dendrogram, hilite them, and inspect data in a table view

Exercise: Clustering- What groups of documents are in the data?- Compute pairwise cosine distances- Apply hierarchical clustering- View dendrogram to find out the number of clusters (k)- Assign k clusters- Apply k-Medoids with k as number of clusters- Select documents of one cluster in dendrogram, hilite them, and inspect data in a table view Reading Textual Data Enrichment Preprocessing Transformation Tagging (POS)Creation ofdocument vectorsFiltering, Stemming, ...Filtering based onoccurrencesRead documents fromclustering data setWITHOUT TITLESRead documents fromclustering data setWITH TITLES Enrichment Transformation Preprocessing I Preprocessing II Table Reader Table Reader Exercise: Clustering- What groups of documents are in the data?- Compute pairwise cosine distances- Apply hierarchical clustering- View dendrogram to find out the number of clusters (k)- Assign k clusters- Apply k-Medoids with k as number of clusters- Select documents of one cluster in dendrogram, hilite them, and inspect data in a table view Reading Textual Data Enrichment Preprocessing Transformation Tagging (POS)Creation ofdocument vectorsFiltering, Stemming, ...Filtering based onoccurrencesRead documents fromclustering data setWITHOUT TITLESRead documents fromclustering data setWITH TITLES Enrichment Transformation Preprocessing I Preprocessing II Table Reader Table Reader

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Created by: Kilian
Created at: 2014-10-20
On NodePit since: 2023-01-17
Last update: 2023-05-29
Created with KNIME version: v4.4.0
Tags: education