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Netflix Recommendation engine contest and relevance for travel

Ram Badrinathan 03/02/2008

All our discussions on the Semantic web and next wave got me thinking when I was reading an article.I was browsing through Wired magazine at Istanbul airport enroute to Berlin and came across an engaging article on the race to build a recommendation engine that is 10% better than Netflix’s. Netflix has a sum of $ 1 million and race has narrowed to 5 teams, one of them being Princeton Alums, others are with AT&T. Anyway one of the more recent entrants is Maths Wiz living in England who is at the forefront of the quest. I am no expert in semantic websearch or human pyschology, but Mr. Potter’s approach ( whose identity was secret) is to integrate the discipline of mathematics and human pyschology. The approach I would guess of arecommendation engine is to data mine the the ratings and movie purchase history of individuals and suggest titles close to what customers interests and needs are. That same principle even for travel. The Internet doesnt differentiate between a search of Richard Branson and Ram Badrinathan typing Luxury holiday in africa. But there are increasing number of travel companies integrating recommendations, profile data to display results closer to your individual expectations. I guess it is a journey. Travelocity allows you to sort reviews based on your lifestage cohort - married with kids, startups like Vibeagent building recommendation engines. But my questions is will Expedia, Trip Advisor come out with a competition for superior recommendation engine for the travel industry

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