Data Acquisition: Difference between revisions

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There seems to be a universal rule for (not only) statistical methods in NLP: '''More data is better data.'''
There seems to be a universal rule for (not only) statistical methods in NLP: '''More data is better data.'''


Translation systems have at their disposal (order of magnitude) more data than a person reads in a lifetime<ref name="inaug">Phillip Koehn. [https://www.youtube.com/watch?v=6UVgFjJeFGY Inaugural lecture.]</ref>.
Translation systems have at their disposal (orders of magnitude) more training data than a person reads in a lifetime<ref name="inaug">Philipp Koehn. [https://www.youtube.com/watch?v=6UVgFjJeFGY Inaugural lecture.]</ref>.
 
<ref name=effectiveness>A. Halevy, P. Norvig, F. Pereira. [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4804817&tag=1 ''The Unreasonable Effectiveness of Data'']</ref>
 
<ref name=friends>Jan Hajič, Eva Hajičová. [http://link.springer.com/chapter/10.1007%2F978-3-540-74628-7_2#page-1 ''Some of Our Best Friends Are Statisticians'']</ref>
 
 
token vs. type


== References ==
== References ==


<references />
<references />

Revision as of 16:07, 23 February 2015

There seems to be a universal rule for (not only) statistical methods in NLP: More data is better data.

Translation systems have at their disposal (orders of magnitude) more training data than a person reads in a lifetime[1].

[2]

[3]


token vs. type

References

  1. ↑ Philipp Koehn. Inaugural lecture.
  2. ↑ A. Halevy, P. Norvig, F. Pereira. The Unreasonable Effectiveness of Data
  3. ↑ Jan Hajič, Eva Hajičová. Some of Our Best Friends Are Statisticians