Comquest: Large Scale User Comment Crawling and Integration-Reference-Cited by-同舟云学术

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Comquest: Large Scale User Comment Crawling and Integration

Published:2024-06-09 Issue: Volume:8 Page:432-435
ISSN:
Container-title:Companion of the 2024 International Conference on Management of Data
language:
Short-container-title:

Author:

Chen Zhijia¹^ORCID,He Lihong²^ORCID,Mukherjee Arjun³^ORCID,Dragut Eduard¹^ORCID

Affiliation:

1. Department of Computer & Information Sciences, Temple University, Philadelphia, USA

2. IBM Almaden Research Center, San Jose, USA

3. Department of Computer Science, University of Houston, Houston, USA

Funder

Army Research Office

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626246.3654736

Reference11 articles.

1. Jumanah Alshehri, Marija Stanojevic, Eduard Dragut, and Zoran Obradovic. 2021. Stay on topic, please: aligning user comments to the content of a news article. In ECIR. Springer, 3--17.

2. Zhijia Chen, Weiyi Meng, and Eduard Dragut. 2022. Web Record Extraction with Invariants. VLDB (2022), 959--972.

3. Alon Halevy and Jane Dwivedi-Yu. 2023. Learnings from Data Integration for Augmented Language Models. arXiv preprint arXiv:2304.04576 (2023).

4. On the dynamics of user engagement in news comment media

5. Lihong He, Chen Shen, Arjun Mukherjee, Slobodan Vucetic, and Eduard Dragut. 2021. Cannot predict comment volume of a news article before (a few) users read it. In ICWSM. 173--184.

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