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Items tagged with "collaborative filtering" (9)

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Blob Datasets for the pack: RCOMM2011 recommender systems...

Created: 2011-05-05 21:18:51 | Last updated: 2011-05-06 12:13:22

Credits: User Matko Bošnjak User Ninoaf

License: Creative Commons Attribution-Share Alike 3.0 Unported License

Dataset description: items This is a concatenated train and test set from ECML/PKDD Discovery Challenge 2011. Only ID and name attributes were used, other attributes are discarded because of the size of the dataset. This example set represents the content information for each of the items represented by an ID. user_history This is an example set consisting of randomly sampled IDs from items dataset. It represents the user's history - all the items (in this case lectures) he has viewed. u...

File type: ZIP archive

Comments: 0 | Viewed: 753 times | Downloaded: 443 times

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Blob Experimental user to item score matrix Excel file

Created: 2011-11-26 20:07:02 | Last updated: 2011-11-26 20:07:04

Credits: User Matko Bošnjak

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 A test file for Collaborative filtering recommender

File type: Excel workbook

Comments: 0 | Viewed: 310 times | Downloaded: 198 times

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Network-member e-LICO Recommender Systems

Unique name: eLICORS
Created: Friday 27 January 2012 13:10:41 (UTC)

 e-LICO Recommender Systems group.

28 shared items   |   0 announcements

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Packs (2)
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Pack Recommender systems workflow templates 2012


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

 The Recommender Extension can be downloaded from the Rapid-I Marketplace from: http://rapidupdate.de:8180/UpdateServer/faces/product_details.xhtml?productId=rmx_irbrecommender . More details can be found: http://elico.rapid-i.com/recommender-extension.html          

12 items in this pack

Comments: 0 | Viewed: 446 times | Downloaded: 136 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

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Workflows (4)

Workflow Collaborative filtering recommender (1)

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This process executes a collaborative filtering recommender based on user to item score matrix. This recommender predicts one user’s score on some of his non scored items based on similarity with other users. The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of recommendations and %{number_of_neighbors} defines the number of the most similar users taken into a...

Created: 2011-03-15 | Last updated: 2012-03-06

Workflow Item-based collaborative filtering recomme... (1)

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The workflow for item-based collaborative filtering receives a user-item matrix for its input, and the same context defined macros as the user-based recommender template, namely %{id}, %{recommendation_no}, and %{number_of_neighbors}. Although this process is in theory very similar to user-based technique, it differs in several processing steps since we are dealing with an item-user matrix, the transposed user-item example set. The first step of the workflow, after declaring zero values miss...

Created: 2011-05-05 | Last updated: 2011-05-09

Credits: User Matko Bošnjak User Ninoaf

Attributions: Blob Datasets for the pack: RCOMM2011 recommender systems workflow templates

Workflow User-based collaborative filtering recomme... (1)

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The workflow for user-based collaborative filtering, takes only one example set as an input: a user-item matrix, where the attributes denote item IDs, and rows denote users. If a user i has rated an item j with a score s, the matrix will have the value s written in i-th row and j-th column. In the context of the process we define the ID of the user %{id}, desired number of recommendations %{recommendation_no}, and the number of neighbors used in ca...

Created: 2011-05-05 | Last updated: 2011-05-09

Credits: User Matko Bošnjak User Ninoaf

Attributions: Blob Datasets for the pack: RCOMM2011 recommender systems workflow templates

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Workflow SVD user-based collaborative filtering rec... (1)

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This workflow takes user-item matrix A as a input. Then it calculates reduced SVD decomposition A_k by taking only k greatest singular values and corresponding singular vectors. This worfkflow calculates recommendations and predictions for particular user %{id} from matrix A. Particular row %{id} is taken from original matrix A and replaced with %{id} row in A_k matrix. Predictions are made for %{id} user based on another users A_k. Note: This workflow uses R-script operator with R library ...

Created: 2011-05-09 | Last updated: 2011-05-09

Credits: User Ninoaf User Matko Bošnjak

Attributions: Workflow User-based collaborative filtering recommender system template Blob Datasets for the pack: RCOMM2011 recommender systems workflow templates

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