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hi i'm jennifer neville thank you for joining me for my talk here at the microsoft research summit i'm a senior principal researcher in the productivity and intelligence group at microsoft research in redmond and today i'm going to talk about extracting pragmatics from content interactions to improve search and recommendation in the enterprise so the goal of this work is really to develop machine learning methods for graphs that will help move us towards more effective personalized search and recommendation systems for searching over things like your personal web or searching over the various modalities of information that you have in an enterprise system and the motivation for using graphs in this space is that often in these more personalized settings the search data that's available to learn how to do search and recommendation is often limited in terms of the number of interactions with the system as well as the content available to to use for the mac

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How to create an eSignature for the extracting semantically related queries by microsoft research

How to create an electronic signature for a PDF online

How to create an electronic signature for a PDF in Google Chrome

How to create an e-signature for signing PDFs in Gmail

How to create an e-signature right from your smartphone

How to create an e-signature for a PDF on iOS

How to create an e-signature for a PDF on Android

How to create an electronic signature for a PDF online

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How to create an electronic signature for a PDF in Google Chrome

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How to create an eSignature for the extracting semantically related queries by microsoft research

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How to create an e-signature right from your smartphone

How to create an e-signature for a PDF on iOS

How to create an e-signature for a PDF on Android

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