Bits 'n Pieces on Big Data
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Bits 'n Pieces on Big Data
Innovative information and insight into Big Data (if you like the content, please consider donating to my bitcoin address #3Pjof6N9xRAYXXSPZ4EAFLfHGn51ZdPcxi)
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It Is Trivially Easy to Match Metadata to Real People

It Is Trivially Easy to Match Metadata to Real People | Bits 'n Pieces on Big Data | Scoop.it

"...We randomly sampled 5,000 numbers from our crowdsourced MetaPhone dataset and queried the Yelp, Google Places, and Facebook directories. With little marginal effort and just those three sources—all free and public—we matched 1,356 (27.1%) of the numbers. Specifically, there were 378 hits (7.6%) on Yelp, 684 (13.7%) on Google Places, and 618 (12.3%) on Facebook..."

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Information Cartography: Creating Zoomable, Large-Scale Maps of Information (KDD 2013)

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Big questions for big data: Stanford’s Jure Leskovec

Big questions for big data: Stanford’s Jure Leskovec | Bits 'n Pieces on Big Data | Scoop.it

Jure Leskovec uses information collected from sites like Twitter, Wikipedia and Facebook to tackle big questions about how society works.

onur savas's insight:

Prof. Leskovec is an expert in information processing using social media. He has many influential papers about modeling and analysis of social networks, and diffusion of information and influence: http://cs.stanford.edu/people/jure/

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Stanford School of Engineering - artificial intelligence | machine learning

Stanford School of Engineering - artificial intelligence | machine learning | Bits 'n Pieces on Big Data | Scoop.it
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AI & ML videos from Andrew Ng...

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