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Items tagged with "recommender system" (9)

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

Created: 05/05/11 @ 21:18:51 | Last updated: 06/05/11 @ 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

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Workflows (5)
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Workflow Content based recommender system template (1)

Created: 05/05/11 @ 21:06:32 | Last updated: 09/05/11 @ 13:40:24

Credits: User Matko Bošnjak User Ninoaf

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

License: Creative Commons Attribution-No Derivative Works 3.0 Unported License

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As an input, this workflow takes two distinct example sets: a complete set of items with IDs and appropriate textual attributes (item example set) and a set of IDs of items our user had interaction with (user example set). Also, a macro %{recommendation_no} is defined in the process context, as a required number of outputted recommendations. The first steps of the workflow are to preprocess those example sets; select only textual attributes of item example set, and set ID roles on both of th...

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Original Uploader

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

Created: 05/05/11 @ 21:07:01 | Last updated: 09/05/11 @ 13:43:09

Credits: User Matko Bošnjak User Ninoaf

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

License: Creative Commons Attribution-No Derivative Works 3.0 Unported License

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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...

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Original Uploader

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

Created: 05/05/11 @ 21:06:45 | Last updated: 09/05/11 @ 13:45:33

Credits: User Matko Bošnjak User Ninoaf

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

License: Creative Commons Attribution-No Derivative Works 3.0 Unported License

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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...

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

Created: 09/05/11 @ 12:45:05 | Last updated: 09/05/11 @ 13:59:45

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

License: Creative Commons Attribution-No Derivative Works 3.0 Unported License

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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 ...

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Viewed: 183 times | Downloaded: 71 times

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Original Uploader

Workflow LSI content based recommender system template (1)

Created: 06/05/11 @ 20:40:24 | Last updated: 09/05/11 @ 13:59:18

Credits: User Ninoaf User Matko Bošnjak

Attributions: Workflow Content based recommender system template Blob Datasets for the pack: RCOMM2011 recommender systems workflow templates

License: Creative Commons Attribution-No Derivative Works 3.0 Unported License

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This workflow performs LSI text-mining content based recommendation. We use SVD to capture latent semantics between items and words and to obtain low-dimensional representation of items. Latent Semantic Indexing (LSI) takes k greatest singular values and left and right singular vectors to obtain matrix  A_k=U_k * S_k * V_k^T. Items are represented as word-vectors in the original space, where each row in matrix A represents word-vector of particular item. Matrix U_k, on the other hand ...

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Packs (3)
Creator

Pack e-LICO recommender workflows


Created: 15/03/11 @ 15:33:48 | Last updated: 28/01/12 @ 19:39:06

This pack contains recommender system workflows created for the purpose of e-LICO project.

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Creator

Pack Recommender systems workflow templates 2012


Created: 08/01/12 @ 12:27:43 | Last updated: 03/06/12 @ 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          

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Pack RCOMM2011 recommender systems workflow templates


Created: 07/04/11 @ 14:59:37 | Last updated: 28/01/12 @ 19:37:47

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Comments: 0 | Viewed: 188 times | Downloaded: 55 times

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