Difference between revisions of "Gravity"
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'''Gravity''' was the name of the [[Netflix Prize]] participants that were part of the team "[[The Ensemble]]", which ranked second overall in the contest. | '''Gravity''' was the name of the [[Netflix Prize]] participants that were part of the team "[[The Ensemble]]", which ranked second overall in the contest. | ||
The team later moved on to found a Budapest-based company that sells recommendation services and personalized advertisement mostly on the European market. | The team later moved on to found a Budapest-based company that sells recommendation services and personalized advertisement mostly on the European market. | ||
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Gravity raised about 1 million US$ venture capital in 2009 and 2010, and raised another 2 million US$ in 2011. | Gravity raised about 1 million US$ venture capital in 2009 and 2010, and raised another 2 million US$ in 2011. | ||
| + | Their products are now marketed under the brand '''Yusp'''. | ||
== Literature == | == Literature == | ||
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== External links == | == External links == | ||
| − | * | + | * https://www.yusp.com/ |
* [[Wikipedia: Gravity Technologies]] | * [[Wikipedia: Gravity Technologies]] | ||
* http://www.marketwatch.com/story/double-netflix-award-grant-for-gravity-2011-09-15 | * http://www.marketwatch.com/story/double-netflix-award-grant-for-gravity-2011-09-15 | ||
[[Category: Company]] | [[Category: Company]] | ||
Latest revision as of 15:26, 3 December 2022
Gravity was the name of the Netflix Prize participants that were part of the team "The Ensemble", which ranked second overall in the contest. The team later moved on to found a Budapest-based company that sells recommendation services and personalized advertisement mostly on the European market. Gravity raised about 1 million US$ venture capital in 2009 and 2010, and raised another 2 million US$ in 2011. Their products are now marketed under the brand Yusp.
Literature
- Joe Sill, Gabor Takacs, Lester Mackey, David Lin: Feature-Weighted Linear Stacking
- I. Pilászy, D. Zibriczky, D. Tikk: Fast ALS-based matrix factorization for explicit and implicit feedback datasets, RecSys 2010.
- Gábor Takács, István Pilászy, Bottyán Németh, Domonkos Tikk: Scalable Collaborative Filtering Approaches for Large Recommender Systems, JMLR
