The problem of how to find relevant content on the web has yet to be solved on a mass scale. You’ve got cyborg news aggregators like Techmeme and Google news and social aggregators like Reddit and Digg competing with Twitter and the Facebook Newsfeed, all of them trying to get you the news that you want to know, as fast as possible.
The Seattle-based Wavii, which has been in super stealth mode until now, takes a different approach to the problem. The startup uses natural language processing and machine learning to parse far corners of the web and bring users personalized content based on their Facebook Likes and feedback. Upon entering Wavii via Facebook Connect, you are asked to pick a combination of 12 topics that pertain to you and rinse, repeat. Wavii picks these initial interests by processing your Facebook Likes, and adjusts itself as you give it more data.
The Seattle-based Wavii, which has been in super stealth mode until now, takes a different approach to the problem. The startup uses natural language processing and machine learning to parse far corners of the web and bring users personalized content based on their Facebook Likes and feedback. Upon entering Wavii via Facebook Connect, you are asked to pick a combination of 12 topics that pertain to you and rinse, repeat. Wavii picks these initial interests by processing your Facebook Likes, and adjusts itself as you give it more data.
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