Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[PRE REVIEW]: LMDiskANN.jl: An Implementation of the Low Memory Disk Approximate Nearest Neighbors Search Algorithm #7936

Open
editorialbot opened this issue Mar 21, 2025 · 7 comments
Labels
Julia pre-review TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning

Comments

@editorialbot
Copy link
Collaborator

Submitting author: @mantzaris (Alexander V. Mantzaris)
Repository: https://github.com/mantzaris/LMDiskANN.jl
Branch with paper.md (empty if default branch): main
Version: v1.0.0
Editor: Pending
Reviewers: Pending
Managing EiC: Chris Vernon

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/467e16d8cc6a29f24b551a3f7e06ab30"><img src="https://joss.theoj.org/papers/467e16d8cc6a29f24b551a3f7e06ab30/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/467e16d8cc6a29f24b551a3f7e06ab30/status.svg)](https://joss.theoj.org/papers/467e16d8cc6a29f24b551a3f7e06ab30)

Author instructions

Thanks for submitting your paper to JOSS @mantzaris. Currently, there isn't a JOSS editor assigned to your paper.

@mantzaris if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

Editor instructions

The JOSS submission bot @editorialbot is here to help you find and assign reviewers and start the main review. To find out what @editorialbot can do for you type:

@editorialbot commands
@editorialbot editorialbot added pre-review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning labels Mar 21, 2025
@editorialbot
Copy link
Collaborator Author

Hello human, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

@editorialbot
Copy link
Collaborator Author

Software report:

github.com/AlDanial/cloc v 1.98  T=0.02 s (673.9 files/s, 98500.6 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Julia                            4            294            323            826
Markdown                         3             48              0            126
YAML                             2              7              0             63
TeX                              1              6              0             37
TOML                             2              4              0             20
-------------------------------------------------------------------------------
SUM:                            12            359            323           1072
-------------------------------------------------------------------------------

Commit count by author:

    16	mantzaris
     3	a.v.mantzaris

@editorialbot
Copy link
Collaborator Author

Paper file info:

📄 Wordcount for paper.md is 481

✅ The paper includes a Statement of need section

@editorialbot
Copy link
Collaborator Author

License info:

✅ License found: MIT License (Valid open source OSI approved license)

@editorialbot
Copy link
Collaborator Author

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- None

🟡 SKIP DOIs

- No DOI given, and none found for title: Freshdiskann: A fast and accurate graph-based ann ...
- No DOI given, and none found for title: Diskann: Fast accurate billion-point nearest neigh...

❌ MISSING DOIs

- 10.1109/bigdata59044.2023.10386517 may be a valid DOI for title: Lm-diskann: Low memory footprint in disk-native dy...
- 10.14778/3476249.3476255 may be a valid DOI for title: A comprehensive survey and experimental comparison...
- 10.1109/34.615448 may be a valid DOI for title: A simple algorithm for nearest neighbor search in ...

❌ INVALID DOIs

- None

@editorialbot
Copy link
Collaborator Author

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

@editorialbot
Copy link
Collaborator Author

Five most similar historical JOSS papers:

scikit-hubness: Hubness Reduction and Approximate Neighbor Search
Submitting author: @VarIr
Handling editor: @terrytangyuan (Retired)
Reviewers: @ryEllison, @aozorahime
Similarity score: 0.6754

LaplaceInterpolation.jl: A Julia package for fast interpolation on a grid
Submitting author: @lootie
Handling editor: @VivianePons (Retired)
Reviewers: @wkearn, @eviatarbach
Similarity score: 0.6751

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs
Submitting author: @diningphil
Handling editor: @arfon (Active)
Reviewers: @idoby, @sepandhaghighi
Similarity score: 0.6665

ClusterValidityIndices.jl: Batch and Incremental Metrics for Unsupervised Learning
Submitting author: @AP6YC
Handling editor: @adi3 (Active)
Reviewers: @rMassimiliano, @malmaud
Similarity score: 0.6602

dml: Distance Metric Learning in R
Submitting author: @terrytangyuan
Handling editor: @arfon (Active)
Reviewers: @joethorley
Similarity score: 0.6539

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Julia pre-review TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning
Projects
None yet
Development

No branches or pull requests

1 participant