Netflix’s Million Dollar Baby Only Expected the Day After Tomorrow?

December 11th, 2008 | by PHC |

For the second year, Netflix has awarded a $50K progress prize. The winning team – BellKor in BigChaos – improved on Netflix’s recommendation algorithm by 9.44%. Although the 10% improvement seems to be getting closer in absolute terms, the last stretch might prove elusive for a little while longer.

Is Netflix’s ground-breaking crowdsourcing approach reaching a limit? Netflix has undeniably got a lot of value out of their contest – 10,000s people working and an algorithmic improvement very close to 10% – for only $100K so far. However, the winning method this year – and the likely research directions for next year – have exponential data and computing power requirements – possibly putting the contest out of reach of most casual researchers.

Are “curated” recommendations superior to pure statistics? Curated recommendations have received some hype lately – from Techmeme’s hiring of an editor to the coincidental launch this week of ClerkDogs – a “clerks-in-a-box” online movie recommendation service? A human touch can certainly rebalance or add a forward-looking perspective to recommendations where data sets are ambiguous (such as clickstream), too small, or lack enough historical data.

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