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CIO Engage: Does the future belong to private clouds? (via CSC Engage Public Community)...

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CIO Debate: The Cyber Buck Stops Everywhere (via CSC)...

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CSC's Paul Scott on Owning the Automotive Customer Communication...

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CSC’s Supply Chain Transformation consulting services assist organizations facing key supply chain challenges...

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Assuming that the desire to whizz around in a car that looks like it came from the 1973 Woody Allen film, 'Sleeper', is strong enough to pay close to more than £35,000 for the privilege, is it really practical? Does our infrastructure support it? And how long would it be before 'range anxiety' (the fear of running out of energy) sets in? (via CSC)...

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The Most Important IT Disruptors of the Last Half Century (via CSC)...

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Securing a Nation in the Information Age (via CSC)...

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Have them in circles
349 people
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BPO in Life Sciences: The New Acquisition Darling? (via CSC)...

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CSC Names Ashish Mahadwar Executive Vice President and General Manager for Strategic Business...

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Competing on Trust (via CSO Online)...

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Bits or pieces?: Agile, Agile ... everywhere (via CSC's @swardley)....

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I'm a huge fan of agile techniques (particularly XP & Scrum). They're very specific methods designed to deal with uncertainty and change whilst maximising the benefit to the customer in terms of achieving their needs. However...
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Using Social Media To Predict Technology Disruptions
Written by: +Ian Wynyard

The purpose of this project was to design a method by which articles could be automatically classified by the technology discussed in their content. The classifications were disruptive and nondisruptive, where disruptive was the positive output. This model was designed to output predictions on the content of articles using text analysis principles in RapidMiner. The methods used to construct this model were gathered  from several internet sources including videos and academic articles. The model utilized a naive Bayes classifier to analyze the content of a training set through which it created weights from that set. The set was then applied to new inputs to create predictions. The model had a sampled accuracy of over 80% with a 4% variance and consistently provided distinction between the disruptive and nondisruptive articles.

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Using_Social_Media_to_Predict_Technology_Disruptions.pdfUsing Social Media to Predict Technology Disruptions April 2014 Author: Ian Wynyard The purpose of this project was to design a method by which articles could be automatically classified by the te 4002 chnology discussed in their content. The classifications were disruptive and nondisruptive, where disruptive was the positive output. This model was designed to output predictions on the content of articles using text analysis principles in Rapi...
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Have them in circles
349 people
Matt Vita's profile photo
Kim Henri V.'s profile photo
Simon Instone's profile photo
Lana Robbins's profile photo
Maksym H's profile photo
Shirley Stamper's profile photo
Christine Silva's profile photo
Susan Paskowitz's profile photo
Richard Brookes's profile photo
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