Workflows

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: Matej Mihelčić Matko Bošnjak

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: Matko Bošnjak

Data iteration workflow (RP) (1)

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This is a data iteration workflow used to iterate throug query update sets.

Created: 2012-01-29

Credits: Matej Mihelčić Matko Bošnjak

Transforming user/item description dataset... (1)

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This workflow provides transformation of an user/item description attribute set, into a format required by attribute based k-NN operators of the Recommender extension. See: http://zel.irb.hr/wiki/lib/exe/fetch.php?media=del:projects:elico:recsys_manual_v1.1.pdf to learn about formats of datasets required by Recommender extension.

Created: 2012-01-30

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

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

Semantic clustering (with alpha-clustering... (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 ("Epistemic" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". This ...

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

Parameter optimization (1)

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This is a parameter optimization workflow for rating prediction recommendation operators.

Created: 2012-02-10 | Last updated: 2012-02-10

Credits: Matej Mihelčić