Author: Domonkos Tikk

Publications

Publication period start: 2012
Number of co-authors: 12

Co-authors

Number of publications with favourite co-authors
Alan Said
2
Gábor Takács
3
István Pilászy
4

Productive Colleagues

Most productive colleagues in number of publications
Nikos Manouselis
5
Alan Said
8
Andreas Hotho
11

Publications

Takács, Gábor, Pilászy, István, Németh, Bottyán, Tikk, Domonkos (2008): Matrix factorization and neighbor based algorithms for the Netflix prize problem. In: Proceedings of the 2008 ACM Conference on Recommender Systems , 2008, . pp. 267-274. https://dx.doi.org/10.1145/1454008.1454049

Pilászy, István, Tikk, Domonkos (2009): Recommending new movies: even a few ratings are more valuable than metadata. In: Proceedings of the 2009 ACM Conference on Recommender Systems , 2009, . pp. 93-100. https://dx.doi.org/10.1145/1639714.1639731

Pilászy, István, Zibriczky, Dávid, Tikk, Domonkos (2010): Fast ALS-based matrix factorization for explicit and implicit feedback datasets. In: Proceedings of the 2010 ACM Conference on Recommender Systems , 2010, . pp. 71-78. https://dx.doi.org/10.1145/1864708.1864726

Takács, Gábor, Pilászy, István, Tikk, Domonkos (2011): Applications of the conjugate gradient method for implicit feedback collaborative filterin. In: Proceedings of the 2011 ACM Conference on Recommender Systems , 2011, . pp. 297-300. https://dx.doi.org/10.1145/2043932.2043987

Said, Alan, Tikk, Domonkos, Hotho, Andreas (2012): The challenge of recommender systems challenges. In: Proceedings of the 2012 ACM Conference on Recommender Systems , 2012, . pp. 9-10. https://dx.doi.org/10.1145/2365952.2365959

Takács, Gábor, Tikk, Domonkos (2012): Alternating least squares for personalized ranking. In: Proceedings of the 2012 ACM Conference on Recommender Systems , 2012, . pp. 83-90. https://dx.doi.org/10.1145/2365952.2365972

Manouselis, Nikos, Said, Alan, Tikk, Domonkos, Hermanns, Jannis, Kille, Benjamin, Drachsler, Hendrik, Verbert, Katrien, Jack, Kris (2012): Recommender systems challenge 2012. In: Proceedings of the 2012 ACM Conference on Recommender Systems , 2012, . pp. 353-354. https://dx.doi.org/10.1145/2365952.2366043

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