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Model update workflow (1)

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This is a Model update workflow called from data iteration workflow on every given query set. In the Loop operator model and current training set are retrieved from the repository. Model update is performed on a given query set creating new model. Model and updated train set are saved in the repository.

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

Credits: Matej Mihelčić Matko Bošnjak

Data iteration workflow (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

Model testing workflow (1)

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This workflow measures performance of three models. Model learned on train data and upgraded using online model updates. Model learned on train data + all query update sets. Model learned on train data only.

Created: 2012-01-29

Credits: Matej Mihelčić

Model saving workflow (1)

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This workflow trains and saves a model for a selected item recommendation operator.

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

Credits: Matej Mihelčić

Recommender workflow (1)

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This is a main online update experimentation workflow. It consists of three Execute Process operators. First operator executes model training workflow. Second operator executes online updates workflow for multiple query update sets. The last operator executes performance testing and comparison workflow. Final performance results are saved in an Excel file.

Created: 2012-01-29

Credits: Matej Mihelčić

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Digital Multimedia Repositories Ontology (DMRO) and ...

Created: 2012-01-29 16:35:26 | Last updated: 2012-01-29 16:38:25

Credits: Lawrynka

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: ZIP archive

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Online update experiment pack

Created: 2012-01-29 16:29:09 | Last updated: 2012-01-29 22:06:46

12 items in this pack

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Loading OWL files (RDF version of videolec... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/). Operator "Build knowledge base" is responsible for collecting data either from OWL files or SPARQL endpoints or RDF repositories and provide it to the subsequent operators in a workflow. In this workflow it is parametrized in this way, that is builds a Sesame/OWLIM repository from the files specified in "Load file" operators. Paths to OWL files are specified as parameter va...

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

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Help for using experimentation workflows with recomm...

Created: 2012-01-29 11:59:49 | Last updated: 2012-01-29 17:28:20

Credits: Matej Mihelčić

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: application/publicationlist

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