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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: Ninoaf Matko Bošnjak

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

LSI content based recommender system template (1)

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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 ...

Created: 2011-05-06 | Last updated: 2011-05-09

Credits: Ninoaf Matko Bošnjak

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

External Tool: Numerically adding two valu... (1)

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The workflow is an examples for the External Tools / UseCase plugin to integrate external tools. It wraps the "bc" command line calculator. Internally, it executes the following script: if [ ! -r "$1" ]; then echo "Cannot read file indicated by first argument '$1'." ; exit -1 ; fi ; if [ ! -r "$2" ];then echo "Cannot read file indicated by second argument '$1'." ; exit -1 ; fi if [ -x /usr/bin/bc ]; then ...

Created: 2011-05-06 | Last updated: 2011-05-06

Credits: Steffen Möller

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Datasets for the pack: RCOMM2011 recommender systems...

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

Credits: Matko Bošnjak Ninoaf

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: ZIP archive

Comments: 0 | Viewed: 773 times | Downloaded: 450 times

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: Matko Bošnjak Ninoaf

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

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: Matko Bošnjak Ninoaf

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

Content based recommender system template (1)

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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...

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

Credits: Matko Bošnjak Ninoaf

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

CGR from multiple fasta files (1)

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 The workflow generates Chaos Game Represenations (CGR) image from multiple fasta files. See http://www.g-language.org/wiki/cgr for more information about the Chaos Game Representations.

Created: 2011-04-29 | Last updated: 2011-04-29

Credits: cory (Kazuki Oshita)

Voronoi polygon generation using GRASS-GIS... (1)

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Generic example on how to deal with vectorial data. Major pitfall is the need to process ProcessOutputs using Xpath plugin. A random point file in GML 2.1.2 is sent to the v.voronoi service and after it is sent to a service that runs v.out.svg generating a SVG image that can be rendered in Taverna (need to set output to SVG image)

Created: 2011-04-27 | Last updated: 2011-04-27

Credits: Jorgejesus