Group: e-LICO Recommender Systems

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 e-LICO Recommender Systems group.

Created at: Friday 27 January 2012 13:10:41 (UTC)

Unique name: eLICORS

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  1. 3840?size=48x48
    Matej Mihelčić shared Hybrid recommender RapidMiner and extension operators
     This pack contains workflow and data for hybrid recommender that is created by combining Recommender extension and RapidMiner built in operators. 
    Thursday 17 May 2012 11:22:10 (UTC)
  2. 3840?size=48x48
    Matej Mihelčić shared Hybrid recommendation system
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    This is one hybrid recommendation system combining linear regression recommender, created using RapidMiner core operators, and Recommender extension multiple collaborative filtering and attribute based operators.
    Thursday 17 May 2012 11:17:45 (UTC)
  3. 3840?size=48x48
    Matej Mihelčić shared MovieLens data for hybrid recommenders
     This is MovieLens data set containing user,item, ratings and item attributes enabling hybrid recommendation system testing. 
    Thursday 17 May 2012 11:06:11 (UTC)
  4. 3840?size=48x48
    Matej Mihelčić shared Parameter optimization
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    This is a parameter optimization workflow for rating prediction recommendation operators.
    Friday 10 February 2012 00:54:06 (UTC)
  5. 1831?size=48x48
    Lawrynka shared Digital Multimedia Repositories Ontology (DMRO) and KB with RDF version of Videolectures.net dataset
    For the information on the ontology see :  http://www.e-lico.eu/?q=node/288 For the information on the original dataset see:    http://www.ecmlpkdd2011.org/challenge.php       The ontology and KB files are zipped into one file.     
    Tuesday 31 January 2012 20:40:15 (UTC)
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    Matej Mihelčić shared Experimentation through repository access
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    This workflow reads train/test dataset from a specified RapidMiner repository and tests selected operator on that datasets. Only datasets specified with a proper regular expression are considered. Train and test data filenames must correspond e.g (train1, test1). Informations about training and testi …
    Tuesday 31 January 2012 16:01:22 (UTC)
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    tomS shared Transforming user/item description datasets into binomial format (RM recommenders)
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    This workflow provides transformation of an user/item description attribute set, into a format required by attribute based k-NN operators of the Recommender extension. See: http://zel.irb.hr/wiki/lib/exe/fetch.php?media=del:projects:elico:recsys_manual_v1.1.pdf to learn about formats of datasets requ …
    Monday 30 January 2012 15:43:00 (UTC)
  8. 3840?size=48x48
    Matej Mihelčić shared Recommender workflow
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    This is a main online update experimentation workflow. It consists of three Execute Process operators. First operator executes model training workflow. Second operator executes online updates workflow for multiple query update sets. The last operator executes performance testing and comparison workfl …
    Monday 30 January 2012 13:16:01 (UTC)
  9. 3840?size=48x48
    Matej Mihelčić shared Model saving workflow
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    This workflow trains and saves a model for a selected item recommendation operator.
    Monday 30 January 2012 13:15:44 (UTC)
  10. 3840?size=48x48
    Matej Mihelčić shared Model testing workflow
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    This workflow measures performance of three models. Model learned on train data and upgraded using online model updates. Model learned on train data + all query update sets. Model learned on train data only.
    Monday 30 January 2012 13:06:01 (UTC)
  11. 1831?size=48x48
    Lawrynka shared Semantic clustering (with alpha-clustering) of SPARQL query results over RDF version of videolectures.net dataset
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    The workflow uses RapidMiner extension named RMonto ( http://semantic.cs.put.poznan.pl/RMonto/ ) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL …
    Monday 30 January 2012 00:15:42 (UTC)
  12. 1831?size=48x48
    Lawrynka shared Semantic clustering (with k-medoids) of SPARQL query results over RDF version of videolectures.net dataset
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    The workflow uses RapidMiner extension named RMonto ( http://semantic.cs.put.poznan.pl/RMonto/ ) to perform clustering of SPARQL query results based on chosen semantic similarity measure. Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". The SPA …
    Sunday 29 January 2012 22:30:37 (UTC)

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