How do I cite this work (academically)?

[cai-lw]

I am using this library in my thesis project and I would like to cite it in my thesis. Beside the library itself, I also want to cite some academic stuff. Are there any academic publication associated with this library? Or do you know about any papers or textbooks that describe your approach of approximate nearest neighbor search?

[erikbern]

Sorry, no, I’m an industry practitioner :)

Think you can just include an URL?

[cai-lw]

@erikbern I just want to know where the random division tree idea comes from. If you learned about it from a course, a book, or even a blog post, I would like to cite them in my work. If you come up with the idea yourself, then it's fine.

[erikbern]

I wrote this library back in 2012, so unfortunately I don't remember, but pretty sure I saw something about it somewhere.

[bartolsthoorn]

For citing the library, we used the following bibtex entry (and it ended up published with this):

@misc{annoy,
  title = {{ANNOY} library},
  howpublished = {\url{https://github.com/spotify/annoy}},
  note = {Accessed: 2017-08-01}
}

(update the accessed date with your own)

[eddelbuettel]

I used the following which produces something closer to what the R Journal, JSS, ... use for CRAN packages:

@Manual{Github:annoy,
  author =       {Erik Bernhardsson},
  title =        {Annoy: Approximate Nearest Neighbors in C++/Python},
  year =         2018,
  note =     {Python package version 1.13.0},
  url =          {https://pypi.org/project/annoy/},
}

The publication really is the PyPi upload, so versioning and dates make some sense. To me at least :grinning:

[erikbern]

makes sense – i can put this in the README.md. does that make sense @eddelbuettel @bartolsthoorn @cai-lw ?

[brianhie]

@cai-lw here's a STOC paper describing random projection trees: http://cseweb.ucsd.edu/~dasgupta/papers/rptree-stoc.pdf This could be what you're looking for?

[serengil]

Please add the bibtex in the read-me. So, academicians will be able to cite it in same way.