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Classic Papers: Articles That Have Stood the Test of Time

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Re: Classic Papers: Articles That Have Stood the Test of Time

#52
post #17
post #2

This has left me scratching my head - why just 2006 ? Having just one year of publications and labeling them "Classic Papers" is pretty misleading as the term is used to indicate a wide gamut of publications over a much longer period of time. It should be just called "Top papers or research from 2006". Unless this expands to at least cover a decade, it shouldn't be labeled as such. This almost sounds like collecting…

> This has left me scratching my head - why just 2006 ? As they said in the post, they're measuring cites 10 years after. It's 2017. I imagine 2006 is their "inaugural year."

Measuring citations by year Y+10 for publication year Y could be run for all historical years pretty easily.

Re: Classic Papers: Articles That Have Stood the Test of Time

#53
This is also very interesting: the AAAI Classic Paper Award.

The AAAI Classic Paper award honors the author(s) of paper(s) deemed most influential, chosen from a specific conference year. Each year, the time period considered will advance by one year.

Papers will be judged on the basis of impact, for example:

    Started a new research (sub)area
    Led to important applications
    Answered a long-standing question/issue or clarified what had been murky
    Made a major advance that figures in the history of the subarea
    Has been picked up as important and used by other areas within (or outside of) AI
    Has been very heavily cited
https://aaai.org/Awards/classic.php

Re: Classic Papers: Articles That Have Stood the Test of Time

#55
post #44

Earlier quoted context omitted.

They were both published in 2006, so not sure what you're getting at. Google Scholar and Sean Henderson are promulgating a false historical record, and there seems to be no way to inform them so that they may correct themselves, other than whining here on HN and hoping they notice. Anybody have any other suggestions?

https://support.google.com/scholar/contact/general

For the record: Re-confirmed that Google Scholar's "support" page is useless. It simply replies with an email indicating that while you can go ahead and complain, they're not going to bother to do anything to fix their algorithm no matter how wrong-headed it is, so tough luck for you and the rest of the unsuspecting, misinformed, current and future universe. Same result as from the previous 3 tries to correct the record. And same as with recent attempts to contact them via email and even USPS snail-mail.

They don't even seem bothered that this in turn leads to Google's own data-miners publishing false results based on Google Scholar's error-filled data; Sean Henderson and Anurag Acharya both have their names on the erroneous blog entry, and still it remains uncorrected. One might think that they would't want their names associated with false information, and messing up the true historical record.

Anyway, congratulations on being presented with ACM SIGACT's 2017 Gödel Prize "for the invention of Differential Privacy" in the "Calibrating Noise to Sensitivity in Private Data Analysis" paper at last week's ACM Symposium on Theory of Computing (STOC). Too bad Google Scholar seems intent on hiding it. Maybe all the search-terms I've semi-awkwardly included here will help future (re)searchers find it, as well as Dwork's "Differential Privacy" ICALP 2006.

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