Workflows

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

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

Offline update recommendation web service (1)

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No description

Created: 2012-05-11

Clustering data from DBpedia using AHC (1)

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 This workflow uses Aglomerative Hierarchical Clustering algorithm to build hierarchy of clusters on data downloaded from DBpedia, the semantic version of Wikipedia. RDF data are downloaded from SPARQL endpoint and merged with DBpedia ontology by "Build Knowledge Base". Set of items to cluster is selected with "SPARQL Selector" and later they are clustered by "Agglomerative Hierarchical Clustering" with distance measure induced by the Bloehdorn Kernel [1]. ...

Created: 2012-05-30 | Last updated: 2012-06-07

Evaluating semantic kernel with k-NN class... (1)

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This workflow uses k-NN classifier to evaluate quality of EL++ Convolution Kernel [1]. As a dataset one of the examples from DL-Learner project [2] is used. After preparing knowledge base with "Build Knowledge Base", the item to item distance matrix is computed with "Calculate Gram/Distance Matrix". Such a matrix is then used as an input to 10-fold cross-validation with k-NN as an classifier and average result is delivered. [1] L. Józefowski, A. Lawrynowicz, J...

Created: 2012-05-30 | Last updated: 2012-06-07

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

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

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

Simple Recommender System Web Service V2 (1)

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No description

Created: 2012-06-20

Instance Selection and Prototype Based Rul... (1)

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Example of Instance selection (Requires Instance Selection and Prototype Based Rules plugin): Before training kNN we do instance selection based on ENN algorithm. The ENN algorithm can be replaced by any other instance selection algorithms from Prules/Selection/* Instance selection algorithms form PRules plugin works as View on original ExampleSet

Created: 2011-11-05 | Last updated: 2011-11-05