Difference between revisions of "User:Zeno Gantner"
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Zeno Gantner (talk | contribs) |
Zeno Gantner (talk | contribs) |
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* [[group recommendation]] | * [[group recommendation]] | ||
* [[Harry Potter effect]] | * [[Harry Potter effect]] | ||
| + | * [[higher-order SVD]] | ||
| + | * [[hybrid recommendation]] | ||
* [[IPTV]] | * [[IPTV]] | ||
* [[item]] | * [[item]] | ||
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* [[news recommendation]] | * [[news recommendation]] | ||
* [[overfitting]] | * [[overfitting]] | ||
| + | * [[pairwise interaction tensor factorization]] | ||
* [[Pearson correlation]] | * [[Pearson correlation]] | ||
* [[personalization]] | * [[personalization]] | ||
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* [[text-based recommendation]] | * [[text-based recommendation]] | ||
* [[time-aware recommendation]] | * [[time-aware recommendation]] | ||
| + | * [[Tucker decomposition]] | ||
* [[user]] | * [[user]] | ||
* [[user model]] | * [[user model]] | ||
* [[video recommendation]] | * [[video recommendation]] | ||
Revision as of 13:08, 6 June 2011
Zeno Gantner from University of Hildesheim, Germany.
- homepage
- Twitter: @zenogantner
I am the main developer of the MyMediaLite recommender system library.
We have currently open PhD/PostDoc positions at our lab: Open positions at ISMLL 2011
Article wishlist
- A/B testing
active learning- attribute-aware recommendation
- attribute-based recommendation
- Bookcrossing
cold-start problemcontent-based filtering- context-aware recommendation
- decision theory
- factorization models
- group recommendation
- Harry Potter effect
- higher-order SVD
- hybrid recommendation
- IPTV
- item
- Jester
- keyword-based recommendation
- kNN
- learning to rank
- location-aware recommendation
- matrix factorization
- news recommendation
- overfitting
- pairwise interaction tensor factorization
- Pearson correlation
- personalization
- personalized search
- ranking
- recommender system
- regularization
- restricted Boltzmann machine
- scalability
- serendipity
- SVD++
- tag
- tag-aware recommendation
- tensor factorization
- text-based recommendation
- time-aware recommendation
- Tucker decomposition
- user
- user model
- video recommendation
