Feature Extraction to Filter Out Low-Quality Answers from Social Question Answering Sites-Reference-Cited by-同舟云学术

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Feature Extraction to Filter Out Low-Quality Answers from Social Question Answering Sites

Published:2022-03-21 Issue: Volume: Page:1-12
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Roy Pradeep Kumar¹^ORCID,Ahmad Zishan²³^ORCID,Singh Jyoti Prakash³^ORCID,Banerjee Snehasish⁴^ORCID

Affiliation:

1. Indian Institute of Information Technology, Surat, 395007, India

2. Indian Institute of Technology, Patna, 801106, India

3. National Institute of Technology Patna, Patna, 800005, India

4. York Management School, University of York, York, YO10 5DD, UK

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2022.2048715

Reference51 articles.

1. Understanding the social evolution of the Java community in Stack Overflow: A 10-year study of developer interactions

2. Social QA in non-CQA platforms

3. Type-Aware Question Answering over Knowledge Base with Attention-Based Tree-Structured Neural Networks

4. The Wisdom of Crowds. .The Wisdom of CrowdsJamesSurowiecki . 306 pp. Random House, New York, 2004. $24.95 (cloth) ISBN 0-385-50386-5; $14.00 (paper) ISBN 0-385-72170-6.

5. So fast so good: An analysis of answer quality and answer speed in community Question-answering sites

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting answer acceptability for question-answering system;International Journal on Digital Libraries;2023-05-05

2. A novel hybrid CNN-LSTM approach for assessing StackOverflow post quality;Journal of Intelligent Systems;2023-01-01

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