26 lines
1.0 KiB
Markdown
26 lines
1.0 KiB
Markdown
type:: [[REVIEWS]]
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tags::
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year:: 2024
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venue:: [[TSE]]
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full-title:: Improving Issue-PR Link Prediction via Knowledge-aware Heterogeneous Graph Learning
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date-start:: [[15-04-2024]] - 16:39
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date-submitted:: [[16-04-2024]]
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external-links:: https://mc.manuscriptcentral.com/tse-cs?URL_MASK=1f9d398417a84b26b4a8d410eacc6fdf
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status:: [[DONE]]
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deadline-submission:: [[19-04-2024]]
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file:: [[@TSE-2023-11-0555.R1]]
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parent:: [[TSE-2023-11-0555_Proof_hi]]
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todoist:: https://app.todoist.com/app/task/tse-2023-11-0555-r1-now-in-your-reviewer-center-7840728063
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- ### [[Highlights]]
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- ### [[Comments]]
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- I thank the authors for their efforts to improve the paper and address all the comments I raised during the first review round. Therefore, I'm satisfied with the given answers.
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- ### [[REVIEWS/Notes]]
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- ### YELLOW CONCERNS
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background-color:: yellow
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- {{query (and [[ffd400]] [[TSE-2023-11-0555.R1]] )}}
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- ### ❓️Questions
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- {{query (and [[question]] [[TSE-2023-11-0555.R1]] )[[question]]}}
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query-table:: true
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query-properties:: [:block]
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