An Approach For Unlabeled Tasks Prioritization
Summary: Neural-network based prioritization of unlabeled software tasks for large backlogs. Novel approach enabling ranking without labeled data; includes model design, empirical results, and implications for data-management-driven task scheduling in enterprises. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Plaksin Yaroslav (Innopolis University)
BibTeX Citation
@inproceedings{yaroslav_sigmod22,
title = {{An Approach For Unlabeled Tasks Prioritization}},
author = {Yaroslav, Plaksin},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3520245},
url = {https://dl.acm.org/doi/10.1145/3514221.3520245},
year = {2022}
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