Travelled to:1 × Ireland
1 × Spain
1 × Switzerland
3 × USA
Collaborated with:I.Pilászy G.Takács A.Said A.Hotho D.Zibriczky S.Dooms B.Loni B.Németh
Talks about:recommend (3) challeng (3) implicit (2) feedback (2) system (2) matrix (2) factor (2) base (2) algorithm (1) neighbor (1)
Person: Domonkos Tikk
DBLP: Tikk:Domonkos
Contributed to:
201420122011201020092008Wrote 7 papers:
- RecSys-2014-SaidDLT #challenge #recommendation
- Recommender systems challenge 2014 (AS, SD, BL, DT), pp. 387–388.
- RecSys-2012-SaidTH #challenge #recommendation
- The challenge of recommender systems challenges (AS, DT, AH), pp. 9–10.
- RecSys-2012-TakacsT #personalisation #ranking
- Alternating least squares for personalized ranking (GT, DT), pp. 83–90.
- RecSys-2011-TakacsPT #collaboration #feedback
- Applications of the conjugate gradient method for implicit feedback collaborative filtering (GT, IP, DT), pp. 297–300.
- RecSys-2010-PilaszyZT #dataset #feedback #matrix #performance
- Fast als-based matrix factorization for explicit and implicit feedback datasets (IP, DZ, DT), pp. 71–78.
- RecSys-2009-PilaszyT #metadata #recommendation
- Recommending new movies: even a few ratings are more valuable than metadata (IP, DT), pp. 93–100.
- RecSys-2008-TakacsPNT #algorithm #matrix #problem
- Matrix factorization and neighbor based algorithms for the netflix prize problem (GT, IP, BN, DT), pp. 267–274.