Papers with Code 아카이브

Question Quality Assessment

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
2
보존된 평가 기록
2

This task expects to build subjective question-answering algorithms to check whether a question is of high quality or needs to be edited/flagged.

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

60k Stack Overflow Questions

The dataset contains 60,000 Stack Overflow questions from 2016-2020, classified into three categories: 1. HQ: High-quality posts without a single edit. 2. LQ_EDIT: Low-quality posts with a negative score, and multiple community edits. However, they still remain open after those changes. 3. LQ_CLOSE: Low-quality posts that were closed by the community without a single edit. ## Notes - Questions are sorted according to Question Id. - Question body is in HTML format. - All dates are in UTC format. - The dataset is also accessible at https://www.kaggle.com/imoore/60k-stack-overflow-questions-with-quality-rate ## How to cite This is an original dataset, published under MIT License. Please cite the dataset for your usage as the following: @article{annamoradnejad2022multiview, title={Multi-View Approach to Suggest Moderation Actions in Community Question Answering Sites}, author={Annamoradnejad, Issa and Habibi, Jafar and Fazli, Mohammadamin}, journal = {Information Sciences}, volume = {600}, pages = {144-154}, year = {2022}, issn = {0020-0255}, doi = {https://doi.org/10.1016/j.ins.2022.03.085}, url = {https://www.sciencedirect.com/science/article/pii/S0020025522003127} }

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