EBay bets $80m on Hunch for smarter product suggestions
Hunch uses inputs from across the web, including social networks, the things its members say they like, other members they follow and answers to Hunch’s own questions, to model an individuals’ taste and make personal recommendations based on their predicted affinity for products and services.
EBay plans to use this technology to move beyond standard item-to-item recommendations – the ‘people who bought this also bought this’ type of approach – to generate “meaningful, yet often non-obvious” recommendations based on the specific tastes of users.
The company is also looking at other applications for the technology, including ways of improving search, advertising and marketing initiatives.

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