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Name: Matej Mihelčić

Joined: Saturday 28 January 2012 21:35:25 (UTC)

Last seen: Saturday 02 April 2016 17:08:22 (UTC)

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Location: Zagreb, Croatia

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Matej Mihelčić has been credited 16 times

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Field/Industry: Computer science and mathematics

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3840?size=60x60 Hr Matej Mihelčić
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Blob MovieLens data for hybrid recommenders

Created: 2012-05-17 11:04:57 | Last updated: 2012-05-17 11:06:10

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 This is MovieLens data set containing user,item, ratings and item attributes enabling hybrid recommendation system testing. 

File type: Trident (Package)

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3840?size=60x60 Hr Matej Mihelčić
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Blob Rating prediction query datasets

Created: 2012-01-29 17:05:46 | Last updated: 2012-01-29 17:07:49

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query sets for online updates of rating prediction operators.

File type: application/x-zip-compressed

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3840?size=60x60 Hr Matej Mihelčić
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Blob Item recommendation query datasets

Created: 2012-01-29 17:02:50 | Last updated: 2012-01-30 13:20:16

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a file containing query datasets for online updates of item recommendation operators.

File type: application/x-zip-compressed

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3840?size=60x60 Hr Matej Mihelčić
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Blob Help for using experimentation workflows with recomm...

Created: 2012-01-29 11:59:49 | Last updated: 2012-01-29 17:28:20

Credits: User Matej Mihelčić

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a help file in how to use experimentation workflows with a recommendation operators.

File type: application/publicationlist

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3840?size=60x60 Hr Matej Mihelčić
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Blob Data example for experimentation with recommender ex...

Created: 2012-01-29 11:53:41 | Last updated: 2012-01-30 13:19:23

Credits: User tomS

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This is a train/test set example used in experimentation. Data in this set consists of three columns, one column for user identification, one for item identification, and one for rating. Every dataset is accompanied with the appropriate aml file. This dataset can be used for rating prediction and item recommendation operator testing. Item recommendation operators will ignore the rating column.

File type: application/x-zip-compressed

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