Difference between revisions of "User:Zeno Gantner"
Jump to navigation
Jump to search
Zeno Gantner (talk | contribs) |
Zeno Gantner (talk | contribs) |
||
| Line 65: | Line 65: | ||
* [[video recommendation]] | * [[video recommendation]] | ||
| − | Companies | + | === Companies === |
* [[Amazon]] | * [[Amazon]] | ||
* [[Commendo]] | * [[Commendo]] | ||
| + | * [[The Echo Nest]] | ||
| + | * [[Filmtipset]] | ||
* [[Google]] | * [[Google]] | ||
* [[Gravity]] | * [[Gravity]] | ||
* [[Hunch]] | * [[Hunch]] | ||
* [[Last.fm]] | * [[Last.fm]] | ||
| + | * [[MoviePilot]] | ||
* [[Netflix]] | * [[Netflix]] | ||
* [[RichRelevance]] | * [[RichRelevance]] | ||
* [[Strands]] | * [[Strands]] | ||
* [[Yahoo]] | * [[Yahoo]] | ||
Revision as of 03:36, 7 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- choice overload
- context-aware recommendation
- decision theory
- Eigentaste
- factorization models
- group recommendation
- Harry Potter effect
- higher-order SVD
hybrid recommendation- hyperparameter
- IPTV
- item
- Jester
- Joke recommendation
- keyword-based recommendation
kNN- learning to rank
- location-aware recommendation
matrix factorization- model
- news recommendation
- overfitting
- pairwise interaction tensor factorization
- parallel factor analysis (PARAFAC), canonical decomposition
- parameter
Pearson correlation- personalization
- personalized search
- product recommendation
- ranking
- recipe recommendation
- recommender system
regularization- restricted Boltzmann machine
- scalability
- serendipity
- similarity
- SVD++
- tag
- tag-aware recommendation
- tensor factorization
- text-based recommendation
- time-aware recommendation
- Tucker decomposition
- user
- user-item matrix
- user model
- user satisfaction
- video recommendation
