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Recommender systems workflow templates 2012

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

12 items in this pack

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Online update recommendation web service V2 (1)

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 After some arbitrary number of recommendations to specific users, system has to update recommendations in item recommendation table. This is accomplished by calling the online update recommendation web service, which updates the recommendation model in RapidAnalytics repository and updates the recommendations for specific users in item recommendation table.

Created: 2012-06-20 | Last updated: 2012-06-20

Offline update recommendation web service V2 (1)

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  Periodically we have to do a full re-training on whole train set by the offline update recommendation web service.

Created: 2012-06-20 | Last updated: 2012-06-20

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Dataset for workflow: "TextualAttributeExtraction fo...

Created: 2012-06-03 19:47:32 | Last updated: 2012-06-04 08:37:05

Credits: Ninoaf

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: application/x-zip-compressed

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TextualAttributeExtraction for Recommender... (1)

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This workflow takes conent data from VideoLectures.Net Recommender System Challenge and extractes word-vectors for each lecture. Latent semantic analysis with Singular Value Decomposition is done on item-word binary matrix. The last step is the binomializaiton of dataset.

Created: 2012-06-03

Online update recommendation web service (1)

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 After some arbitrary number of recommendations to specific users, system has to update recommendations in \textit{item recommendation table}. This is accomplished by calling the online update recommendation web service, which updates the recommendation model in RapidAnalytics repository and updates the recommendations for specific users in \textit{item recommendation table}.

Created: 2012-05-11 | Last updated: 2012-05-11

Write activity web service (1)

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 When the specific user $i$ "consumes" certain item $j$ the write activity web service is called, which writes activity $(i,j)$ to \textit{train set table} and removes recommendation $j$ for user $i$ from \textit{item recommendation table} in SQL database.

Created: 2012-05-11 | Last updated: 2012-05-11

Front-end Recommendation Web Service (1)

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 Front-end recommendation web service has a simple job to query the cached recommendations from the \textit{item recommendation table}

Created: 2012-05-11 | Last updated: 2012-05-11

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Recommender system engine in RapidAnalytics

Created: 2012-05-11 12:54:44 | Last updated: 2012-06-20 14:47:43

9 items in this pack

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Dataset for Simple RS Web Service

Created: 2012-05-10 12:01:26 | Last updated: 2012-05-10 12:01:27

Credits: Ninoaf

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: Trident (Package)

Comments: 0 | Viewed: 27 times | Downloaded: 13 times

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