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Rescooped by luiy from Politique des algorithmes
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Google has #open sourced a #tool for inferring cause from correlations | #algorithms #datascience

Google has #open sourced a #tool for inferring cause from correlations | #algorithms #datascience | Public Datasets - Open Data - | Scoop.it
Google open sourced a new package for the R statistical computing software that’s designed to help users infer whether a particular action really did cause subsequent activity. Google has been using the tool, called CausalImpact, to measure AdWords campaigns but it has broader appeal.

Via Dominique Cardon
luiy's insight:

Google announced on Tuesday a new open source tool that can help data analysts decide if changes to products or policies resulted in measurable change, or if the change would have happened anyway. The tool, called CausalImpact, is a package for the R statistical computing software, and Google details it in a blog post.

 

According to blog post author Kay H. Brodersen, Google uses the tool — created it, in fact — primarily for quantifying the effectiveness of AdWords campaigns. However, he noted, the same method could be used to gauge everything from whether adding a new feature caused an increase in app downloads to questions involving events in medical, social or political science.

 

http://google.github.io/CausalImpact/

 

 

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Scooped by luiy
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Web Data Commons - Hyperlink Grap Extracting the Hyperlink Graph from the Common Web Crawl l #opendata

Web Data Commons - Hyperlink Grap Extracting the Hyperlink Graph from the Common Web Crawl l #opendata | Public Datasets - Open Data - | Scoop.it
luiy's insight:

This page provides a large hyperlink graph for public download. The graph has been extracted from the Common Crawl 2012 web corpus and covers 3.5 billion web pages and 128 billion hyperlinks between these pages. To the best of our knowledge, the graph is the largest hyperlink graph that is available to the public outside companies such as Google, Yahoo, and Microsoft. Below we provide instructions on how to download the graph as well as basic statistics about its topology.

We hope that the graph will be useful for researchers who develop

search algorithms that rank results based on the hyperlinks between pages.SPAM detection methods which identity networks of web pages that are published in order to trick search engines.graph analysis algorithms and can use the hyperlink graph for testing the scalability and performance of their tools.Web Science researchers who want to analyze the linking patterns within specific topical domains in order to identify the social mechanisms that govern these domains.

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Rescooped by luiy from Big Data : Digital Assets to Evaluate, Protect and Value
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7 ways #BigData could revolutionize life | #health #hadoop #algorithms

7 ways #BigData could revolutionize life | #health #hadoop #algorithms | Public Datasets - Open Data - | Scoop.it
7 ways Big Data could revolutionize life by 2020 #infographic | See more about big data.

Via C. CHAMBET-FALQUET
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