Data narratives for result: Clustering Result1475981346023

Data Narrative 1: Execution view     

 

The Understanding User Activity method was run on dataset File.txt (input DocumentsToFilter) and dataset stop W.txt (input DocumentsToFilter), with MINNUMBEROFCLUSTERS1475981346023 set to 5. The Clustering Result1475981346023 results are stored online.

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Data Narrative 2: Data view     

 

The Clustering Result1475981346023 results have been derived from the dataset File.txt (input DocumentsToFilter) and dataset stop W.txt (input DocumentsToFilter).

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Data Narrative 3: Method view     

 

The method Understanding User Activity performs a single main type of analysis on the input dataset through the Clustering step. First, the input data is analyzed by Remove Report Data (a type of Filter step), followed by Merge Document Collection (a type of Combine step). The final results are produced by Clustering (a type of Analysis step).

The Clustering Result1475981346023 results are the product of the Clustering (a type of Analysis step).

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Data Narrative 4: Dependency view     

 

The method Understanding User Activity has 3 steps. Their dependency view is specified as follows. First, the input data is analyzed by Remove Report Data, followed by Merge Document Collection (using data from Remove Report Data). The final results are produced by Clustering (using data from Merge Document Collection).

The Clustering Result1475981346023 results are the product of Clustering.

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Data Narrative 5: Implementation view     

 

The method Understanding User Activity has 3 steps. They are implemented as follows (showing in brackets the general step they implement, if any). First, the input data is analyzed by Remove Report Data, followed by Join Reports (implementation of Merge Document Collection). The final results are produced by K Means (implementation of Clustering).

The Clustering Result1475981346023 results are the product of K Means.

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Data Narrative 6: Software view     

 

The method Understanding User Activity has 3 steps. First, the input data is analyzed by Remove Report Data, followed by Join Reports. The final results are produced by K Means. The steps use the following software:

K Means uses a bash script program to perform its functionality.The software is licensed under a GPLv2 license.
Remove Report Data uses a bash script program to perform its functionality.
Join Reports uses a bash script program to perform its functionality.

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