Difference between revisions of "User:Zeno Gantner"
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* [[decision theory]] | * [[decision theory]] | ||
* [[Eigentaste]] | * [[Eigentaste]] | ||
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* [[exploration vs. exploitation]] | * [[exploration vs. exploitation]] | ||
* [[factorization models]] | * [[factorization models]] | ||
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* [[FAQ for recommender system users]] | * [[FAQ for recommender system users]] | ||
* [[Filter bubble]] | * [[Filter bubble]] | ||
| + | * [[Flixster dataset]] | ||
* <s>[[group recommendation]]</s> | * <s>[[group recommendation]]</s> | ||
* [[Harry Potter effect]] | * [[Harry Potter effect]] | ||
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* [[Facebook]] | * [[Facebook]] | ||
* [[Filmtipset]] | * [[Filmtipset]] | ||
| + | * [[Flixster]] | ||
* [[Google]] | * [[Google]] | ||
* [[Gravity]] | * [[Gravity]] | ||
Revision as of 07:20, 12 September 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
- bandit
- BookCrossing
- Category:File format
- CHI
- choice overload
- CofiRank
cold-start problem- computational advertising
content-based filtering- context
- context-aware recommendation
- decision theory
- Eigentaste
- Epinions dataset
- exploration vs. exploitation
- factorization models
- FAQ for recommender system developers
- FAQ for recommender system users
- Filter bubble
- Flixster dataset
group recommendation- Harry Potter effect
- HCI
- higher-order SVD
hybrid recommendation- hyperparameter
- incentive
- information retrieval
- Introduction to recommender systems
- Introduction to recommender system algorithms
- IPTV
- item
- IUI: IUI 2010, IUI 2011, IUI 2012
- Jester
- Joke recommendation
- KDD Cup
- KDD: KDD 2007, KDD 2008, KDD 2009, KDD 2010
- KDD Cup 2010
- keyword-based recommendation
kNN- learning
- learning to rank
- location-aware recommendation
- long tail
- MAP
- Markov chain
- Markov decision process, MDP
matrix factorization- mean average precision
- mean reciprocal rank
- Million Song Dataset
- model
- monetization
- Movie Hack Day
- multi-arm bandit
- Music Hack Day
NDCG- news recommendation
- overfitting
- pairwise interaction tensor factorization
- parallel factor analysis (PARAFAC), canonical decomposition
- parameter
Pearson correlation- personalization
- personalized advertising
- personalized search
- product recommendation
- ranking
- recipe recommendation
- recommendation of financial products
recommender system- reinforcement learning
regularization- reputation
- restricted Boltzmann machine
- review
- scalability
- serendipity
- similarity
- software as a service
- software recommendation
- SVD
- SVD++, SVDPlusPlus
- TaFeng
- tag
- tag-aware recommendation
- tensor factorization
- text-based recommendation
- text mining
- time-aware recommendation
- Tucker decomposition
- TV program recommendation
- UMAP: UMAP 2010,
UMAP 2011, UMAP 2012 - user
- user-item matrix
- user model
- user recommendation
- user satisfaction
- video recommendation
- web service
- WSDM: WSDM 2010, WSDM 2011, WSDM 2012
Companies
- Amazon
- Commendo
- EBay
- The Echo Nest
- Filmtipset
- Flixster
- Gravity
- Hunch
- Last.fm
- MoviePilot
- Netflix
- Pandora
- RichRelevance
- Scarab Research
- Strands
- TiVo
- Yahoo
RecSys slides, classes, etc.
Personal TODO list
- rename remaining plural categories
- (after some time) remove the old plural categories
