DiversiNews: Enriching News Consumption with Relevant Yet Diverse News Articles Retrieval
Summary: DiversiNews uses semantic text embeddings and Diversity-aware k-MIPS to return news that are both relevant and diverse. Novelty: integrating Dk-MIPS into scalable retrieval to balance relevance versus viewpoint diversity and mitigate echo chambers. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yiqun Sun (National University of Singapore)
- 2. Qiang Huang (National University of Singapore)
- 3. Yanhao Wang (East China Normal University)
- 4. Anthony K. H. Tung (National University of Singapore)
BibTeX Citation
@article{sun_vldb24,
title = {{DiversiNews: Enriching News Consumption with Relevant Yet Diverse News Articles Retrieval}},
author = {Sun, Yiqun and Huang, Qiang and Wang, Yanhao and Tung, Anthony K. H.},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4277--4280},
doi = {10.14778/3685800.3685854},
url = {https://doi.org/10.14778/3685800.3685854},
year = {2024}
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