

List of Important Publications in Computer Science - vinutheraj
http://en.wikipedia.org/wiki/List_of_important_publications_in_computer_science

======
danieldk
In some areas the list is certainly not accurate. E.g. in computational
linguistics:

\- _Realization of Natural-Language Interfaces Using Lazy Functional
Programming_ , Frost, 2006. I never ever heard of this article, with only 17
citations overall (in 5 years) it can hardly be considered important.

\- In the entry of _Transformation-based error-driven learning and natural
language processing_ , Brill, 1995 (which is an important publication) it is
stated that it _"Describes a now commonly-used POS tagger based on
transformation-based learning."_ Which is not true, since nearly everyone uses
HMM, maxent, or SVM taggers these days because they give far higher
accuracies.

Although it is far from perfect, the number of citations is probably one of
the best manners to count importance. Someone actually did this per year for
ACL conferences:

<http://www.phontron.com/blog/?p=29>

Obviously, there are other conferences, journals, etc. But it gives a pretty
good overview of papers that are recommended. Also, there's the ACL top-10
rankings:

<http://clair.si.umich.edu/clair/anthology/rankings.cgi>

------
rxin
I took a look at the area that I am familiar with (database). If you'd like to
gain more understanding about the area, it's probably better to look at
required reading list from Berkeley and Stanford. (Note that the Berkeley list
is longer.)

<http://www.eecs.berkeley.edu/GradAffairs/CS/Prelims/db.html>

<http://infolab.stanford.edu/db_pages/infoquallist.html>

------
epo
Striking how old most of these papers are, many from the 60s and 70s, very few
from the 00s.

Those who don't learn from the past are destined to reinvent it, poorly.

~~~
Goladus
Some of the criteria are biased towards older papers. Influence is extremely
biased-- it's rare for a paper to change the world immediately. Future
influential papers written today may not actually earn the label for another
10-20 years. Breakthroughs and introductions are somewhat biased in general,
but especially biased in computer science given the youth of the field and the
fact that access to computers was rare and difficult before the 60s.

"Latest and greatest" is not biased, in theory, but in practice it can be a
lot harder to identify what truly is the latest and greatest as opposed to
what is merely the most popular.

------
jackpirate
If you're an aspiring computer science researcher looking at these articles, I
cannot recommend enough Hamming's speach "You and Your Research."
(<http://www.cs.virginia.edu/~robins/YouAndYourResearch.html>)

He talks about the little optimizations you can do in your life to take your
research to world-class level.

