Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries-Reference-Cited by-同舟云学术

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Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries

Published:2019-11-07 Issue:CSCW Volume:3 Page:1-28
ISSN:2573-0142
Container-title:Proceedings of the ACM on Human-Computer Interaction
language:en
Short-container-title:Proc. ACM Hum.-Comput. Interact.

Author:

Dash Abhisek¹,Shandilya Anurag²,Biswas Arindam³,Ghosh Kripabandhu⁴,Ghosh Saptarshi³,Chakraborty Abhijnan⁵

Affiliation:

1. Indian Institute of Technology, Kharagpur, India

2. IIT Kharagpur, Kharagpur, West Bengal, India

3. Indian Institute of Technology Kharagpur, Kharagpur, India

4. Indian Institute of Technology, Kanpur, India, Kanpur, India

5. Max Planck Institute for Software Systems, Saarbrucken, Germany

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Link

https://dl.acm.org/doi/pdf/10.1145/3359274

Reference68 articles.

1. MCMR: Maximum coverage and minimum redundant text summarization model

3. Streaming submodular maximization

4. Bias on the web

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