Closed MatthewMiddlehurst closed 1 year ago
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I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.
I also found the following external resources that might be helpful:
Summaries of links found in the content:
From looking through the relevant snippets, I decided to make the following modifications:
File Path | Proposed Changes |
---|---|
docs/papers_using_aeon.md |
Modify docs/papers_using_aeon.md with contents: • Navigate to the "Clustering" section in the file. • Check if a subsection for the year the paper was published exists. If not, create a new subsection for the year. • Under the appropriate subsection, add the new publication in the Harvard style reference format: "Author(s). (Year). Title. Journal. DOI/URL" • The reference should look like this: "Middlehurst, M., Vickers, W., & Bagnall, A. (2023). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems. https://link.springer.com/article/10.1007/s10115-023-01952-0" |
I have created a plan for writing the pull request. I am now working my plan and coding the required changes to address this issue. Here is the planned pull request:
Update papers_using_aeon.md with new publication for time series clustering
sweep/update-papers-using-aeon
Description
This PR updates the
papers_using_aeon.md
documentation page in thedocs
directory. It adds a new publication in the Harvard style reference format for the paper "A review and evaluation of elastic distance functions for time series clustering". The publication can be found at this link.Summary of Changes
- Added a new subsection for the year the paper was published under the "Clustering" section in
papers_using_aeon.md
.- Added the new publication in the Harvard style reference format: "Middlehurst, M., Vickers, W., & Bagnall, A. (2023). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems. https://link.springer.com/article/10.1007/s10115-023-01952-0"
File | Instructions | Progress | Error logs |
---|---|---|---|
docs/papers_using_aeon.md |
Modify docs/papers_using_aeon.md with contents: • Navigate to the "Clustering" section in the file. • Check if a subsection for the year the paper was published exists. If not, create a new subsection for the year. • Under the appropriate subsection, add the new publication in the Harvard style reference format: "Author(s). (Year). Title. Journal. DOI/URL" • The reference should look like this: "Middlehurst, M., Vickers, W., & Bagnall, A. (2023). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems. https://link.springer.com/article/10.1007/s10115-023-01952-0" |
✅ Commit d03b825 |
No errors. |
Here are my self-reviews of my changes at sweep/update-papers-using-aeon
.
Here is the 1st review
Thanks for your contribution. There is just one small change that needs to be made:
- In the file
docs/papers_using_aeon.md
, it seems like the introductory paragraph has been repeated at the end of your changes (lines 9-11). Please remove this repetition.Once this change is made, everything should be good to go!
I finished incorporating these changes.
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Update the
/docs/papers_using_aeon.md
page with a Harvard style reference for the paper "A review and evaluation of elastic distance functions for time series clustering" from https://link.springer.com/article/10.1007/s10115-023-01952-0.The entry should be under the section "Clustering" with a subsection for the year the publication was published.
Checklist
- [X] `docs/papers_using_aeon.md` > • Navigate to the "Clustering" section in the file. > • Check if a subsection for the year the paper was published exists. If not, create a new subsection for the year. > • Under the appropriate subsection, add the new publication in the Harvard style reference format: "Author(s). (Year). Title. Journal. DOI/URL" > • The reference should look like this: "Middlehurst, M., Vickers, W., & Bagnall, A. (2023). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems. https://link.springer.com/article/10.1007/s10115-023-01952-0"