Countdown to PDC09: Big Brains Descend Upon PDC and Teach Us How to Dream
Description
Today a new experiment comes out of Redmond in the form of a new toolbar for Internet Explorer that analyzes the web pages you are looking at and applies what it sees to your social networks. This means the proper nouns and contextual references in the
sites you're looking at are matched up to the things your friends might be talking about. So if you're browsing a movie review, you may see what a friend wrote about that movie as an inline contextual update.
Emre Kiciman and CK Wang from Microsoft Research joined us at the Channel 9 studio to talk about the Social Web toolbar and how it works. You can download the Social Web Experience Toolbar for IE here.
Emre Kiciman and CK Wang from Microsoft Research joined us at the Channel 9 studio to talk about the Social Web toolbar and how it works. You can download the Social Web Experience Toolbar for IE here.
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The Discussion
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prasannap 1. Would love to ALSO see consolidated list of information for the page that I visit insted of just individual Link that I need to hyperlink
2. Great tool. Any easy ways I can also get info. about the pages that my friends visit to get their information. I know you DO NOT have to share the info. about who visited which page, but would love to see on a specific day which was the MAX # for all the pages visited within my friend circle
3. Anyway for us to rate the content so that I see the hottest topic at that split moment
In short I would like to see the MOST Important & MOST Valuable information
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tonyso The examples shown here are consumer-focus, when can we see and IT Pro/Dev focus for this? Are the buckets that the tool looks in fixed or programmable?
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Emre K.dot Hi Tony,
What do you mean by buckets?
The matching between social network messages and the web pages is open-ended. We use 2 algorithms in our tool to do the matching, and 1 is trained on wikipedia and recognizes the kinds of things talked about in wikipedia pretty smartly; the other technique is a context-free matching algorithm on n-grams. The former gives better results and we rank those matches higher. But neither technique is limited to consumer scenarios.
I think the trick to getting this to work for specialized scenarios will be making sure that you have the data you care about available in the social network.