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Blob Data example for experimentation with recommender ex...

Created: 2012-01-29 11:53:41 | Last updated: 2012-01-30 13:19:23

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a train/test set example used in experimentation. Data in this set consists of three columns, one column for user identification, one for item identification, and one for rating. Every dataset is accompanied with the appropriate aml file. This dataset can be used for rating prediction and item recommendation operator testing. Item recommendation operators will ignore the rating column.

File type: application/x-zip-compressed

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Workflow Operator testing workflow (1)

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This workflow is used for operator testing. It joins dataset metafeatures with execution times and performanse measures of the selected recommendation operator. In the Extract train and Extract test Execute Process operator user should open Metafeature extraction workflow. In the Loop Operator train/test data are used to evaluate performanse of the selected operator. Result is remebered and joined with the time and metafeature informations. This workflow can be used both for Item Recommend...

Created: 2012-01-29

Credits: User Matej Mihelčić User Matko Bošnjak

Workflow Metafeature extraction (1)

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This is a metafeature extraction workflow used in Experimentation workflow for recommender extension operators. This workflow extracts metadata from the train/test datasets (user/item counts, rating count, sparsity etc). This workflow is called from the operator testing workflow using Execute Process operator.

Created: 2012-01-29 | Last updated: 2012-01-30

Credits: User Matko Bošnjak

Workflow Iterate through datasets (1)

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This is a dataset iteration workflow. It is a part of Experimentation workflow for recommender extension. Loop FIles operator iterates through datasets from a specified directory using read aml operator. Only datasets specified with a proper regular expression are considered. Train and test data filenames must correspond e.g (train1.aml, test1.aml). In each iteration Loop Files calles specified operator testing workflow with Execute subprocess operator. Informations about training and t...

Created: 2012-01-29

Credits: User Matej Mihelčić User Matko Bošnjak

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Workflow Semantic clustering (with AHC) of SPARQL q... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Common classes" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". ...

Created: 2012-01-29 | Last updated: 2012-01-29

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Workflow Semantic clustering (with k-medoids) of SP... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". The SPARQL query is entered in a parameter of "SPARQL selector" operator. The clustering operator (k-medoids) allows to specify which of the query variables are to be used as clustering criteria. If more ...

Created: 2012-01-29

Pack Experimentation for recommender extension templates


Created: 2012-01-28 21:54:16 | Last updated: 2012-01-31 16:01:43

This is a recommender extension experimentation pack

6 items in this pack

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Pack RCOMM2011 recommender systems workflow templates


Created: 2011-04-07 14:59:37 | Last updated: 2012-01-28 19:37:47

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6 items in this pack

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