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Items tagged with "recommendation" (22)

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Files (5)

Blob Rating prediction query datasets

Created: 2012-01-29 17:05:46 | Last updated: 2012-01-29 17:07:49

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query sets for online updates of rating prediction operators.

File type: application/x-zip-compressed

Comments: 0 | Viewed: 39 times | Downloaded: 36 times

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Blob Item recommendation query datasets

Created: 2012-01-29 17:02:50 | Last updated: 2012-01-30 13:20:16

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query datasets for online updates of item recommendation operators.

File type: application/x-zip-compressed

Comments: 0 | Viewed: 54 times | Downloaded: 57 times

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Blob Help for using experimentation workflows with recomm...

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

Credits: User Matej Mihelčić

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a help file in how to use experimentation workflows with a recommendation operators.

File type: application/publicationlist

Comments: 0 | Viewed: 42 times | Downloaded: 43 times

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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

Comments: 0 | Viewed: 74 times | Downloaded: 68 times

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Blob MovieLens data for hybrid recommenders

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

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 This is MovieLens data set containing user,item, ratings and item attributes enabling hybrid recommendation system testing. 

File type: Trident (Package)

Comments: 0 | Viewed: 148 times | Downloaded: 135 times

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Packs (3)

Pack Online update experiment pack


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

This is a pack containing experimentation workflows and datasets for item recommendation and rating prediction online update testing.

12 items in this pack

Comments: 0 | Viewed: 68 times | Downloaded: 46 times

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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

Comments: 0 | Viewed: 68 times | Downloaded: 39 times

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Pack Hybrid recommender RapidMiner and extension operators


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

 This pack contains workflow and data for hybrid recommender that is created by combining Recommender extension and RapidMiner built in operators. 

2 items in this pack

Comments: 0 | Viewed: 112 times | Downloaded: 71 times

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Workflows (14)

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 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: User Matej Mihelčić User Matko Bošnjak

Workflow 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: User Matej Mihelčić 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

Workflow 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: User Matej Mihelčić

Workflow 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: User Matej Mihelčić

Workflow 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: User Matej Mihelčić

Workflow 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: User Matej Mihelčić User Matko Bošnjak

Workflow 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: User Matej Mihelčić

Workflow recommender workflow (RP) (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: User Matej Mihelčić

Workflow Model testing workflow (RP) (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 | Last updated: 2012-01-30

Credits: User Matej Mihelčić

Workflow Model saving workflow (RP) (1)

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This workflow trains and saves model for a selected rating prediction operator.

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

Credits: User Matej Mihelčić

Workflow 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: User Matej Mihelčić User Matko Bošnjak

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Linked Data

Non-Information Resource URI: http://www.myexperiment.org/tags/3231


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