Content from the e-LICO Recommender Systems group

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Recommender systems workflow templates 2012

Created: 2012-01-08 12:27:43 | Last updated: 2012-06-03 19:48:22

12 items in this pack

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Hybrid recommendation system (1)

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This is one hybrid recommendation system combining linear regression recommender, created using RapidMiner core operators, and Recommender extension multiple collaborative filtering and attribute based operators.

Created: 2012-05-17

Credits: Matej Mihelčić Matko Bošnjak

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MovieLens data for hybrid recommenders

Created: 2012-05-17 11:04:57 | Last updated: 2012-05-17 11:06:10

Credits: tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: Trident (Package)

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Hybrid recommender RapidMiner and extension operators

Created: 2012-05-17 10:57:03 | Last updated: 2012-05-17 11:13:51

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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

Experimentation through repository access (1)

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This workflow reads train/test dataset from a specified RapidMiner repository and tests selected operator on that datasets. Only datasets specified with a proper regular expression are considered. Train and test data filenames must correspond e.g (train1, test1). Informations about training and testing data, performanse measures of a selected operator are stored as an Excel file. Note: Train/test file names should not be contained in the repository path. E.g training/train is not a god path,...

Created: 2012-01-31 | Last updated: 2012-02-01

Credits: Matej Mihelčić Matko Bošnjak tomS

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

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

Model update workflow (RP) (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: 2012-01-30

Credits: Matej Mihelčić