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Hadoop london

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An evening with Hadoop in London

An evening with Hadoop in London

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  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.
  • With 600 million people visiting Yahoo!, 11 billion times a month, generating 98 billion page views, Yahoo! is a leader in many categories, and people trust Yahoo! to give them a great experience and to show them what’s most interesting and relevant to them.

    [ON CLICK] We serve about 3 million different versions of the Today Module every 24 hours. Behind every click, we’re using Hadoop to optimize what you see on Yahoo.com. That personalization is necessary because a user’s trust in us to deliver relevance is invaluable.

    Hadoop allows us to analyze story clicks by applying machine learning so we can figure out what you like and give you more of it. The amount of data we process to make that happen is unbelievable, and Eric will go into more detail on this in a minute. 

    Every click a person makes on our homepage – that’s around half a billion clicks per day – results in multiple personalized rankings being computed, each completing in less than 1/100th of a second.

    Within ~7 minutes of a user clicking on a story, our entire ranking model is updated. You see why we can’t live without Hadoop…

    Our Content Optimization Engine creates a real-time feedback loop for our editors. They can serve up popular stories and pull out unpopular stories, based on what the algorithm is telling them in real time.

    Our modeling techniques help us understand the DNA of the content and eliminate the guesswork, so we can actually predict a story’s relevance and popularity with our audience.