Tag Results

Items tagged with "user-based" (3)

Note: some items may not be visible to you, due to viewing permissions.

Files (1)

Uploader

Matko BoÅ¡njak

View

Download

Datasets for the pack: RCOMM2011 recommender systems...

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

Credits: Matko BoÅ¡njak 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: 770 times | Downloaded: 448 times

Tags:

Workflows (2)

RapidMiner

Uploader

Matko BoÅ¡njak

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

Download

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: Matko BoÅ¡njak Ninoaf

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

RapidMiner

Uploader

Ninoaf

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

Download

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: Ninoaf Matko BoÅ¡njak

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

What is this?

Linked Data

Non-Information Resource URI: http://www.myexperiment.org/tags/2626

Alternative Formats