{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T06:40:16Z","timestamp":1735627216209,"version":"3.32.0"},"reference-count":15,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:p>\n            In the digital age, where echo chambers on social media and news platforms increasingly shape public opinion, there is a growing need for tools that present news consumers with a broad spectrum of perspectives. To this end, we introduce DiversiNews, a novel system designed to diversify news consumption by providing readers with articles that are not only relevant to their interests but also offer a variety of viewpoints. DiversiNews leverages state-of-the-art semantic text encoding techniques and implements advanced Diversity-aware\n            <jats:italic>k<\/jats:italic>\n            -Maximum Inner Product Search (D\n            <jats:italic>k<\/jats:italic>\n            MIPS) algorithms. Our demonstration highlights the potential of DiversiNews to broaden users' exposure to different viewpoints, thereby countering the polarizing effect of digital echo chambers. We showcase how DiversiNews can enrich the news reading experience, supporting the development of a more informed and balanced public discourse in digital news consumption applications.\n          <\/jats:p>","DOI":"10.14778\/3685800.3685854","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"4277-4280","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["DiversiNews: Enriching News Consumption with Relevant Yet Diverse News Articles Retrieval"],"prefix":"10.14778","volume":"17","author":[{"given":"Yiqun","family":"Sun","sequence":"first","affiliation":[{"name":"National University of Singapore"}]},{"given":"Qiang","family":"Huang","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]},{"given":"Yanhao","family":"Wang","sequence":"additional","affiliation":[{"name":"East China Normal University"}]},{"given":"Anthony K. H.","family":"Tung","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Article 30","author":"A\u00efmeur Esma","year":"2023","unstructured":"Esma A\u00efmeur, Sabrine Amri, and Gilles Brassard. 2023. Fake news, disinformation and misinformation in social media: a review. Soc. Netw. Anal. Min. 13, 1, Article 30 (2023), 36 pages."},{"volume-title":"Defining misinformation, disinformation and malinformation: An urgent need for clarity during the COVID-19 infodemic. Discussion Papers 20--06. Department of Economics","author":"Baines Darrin","key":"e_1_2_1_2_1","unstructured":"Darrin Baines and Robert J R Elliott. 2020. Defining misinformation, disinformation and malinformation: An urgent need for clarity during the COVID-19 infodemic. Discussion Papers 20--06. 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Rewiring What-to-Watch-Next Recommendations to Reduce Radicalization Pathways. In WWW. 2719--2728.","DOI":"10.1145\/3485447.3512143"},{"key":"e_1_2_1_8_1","unstructured":"Tianyu Gao Xingcheng Yao and Danqi Chen. 2021. SimCSE: Simple Contrastive Learning of Sentence Embeddings. In EMNLP. 6894--6910."},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Qiang Huang and Anthony Tung. 2023. Lightweight-Yet-Efficient: Revitalizing Ball-Tree for Point-to-Hyperplane Nearest Neighbor Search. In ICDE. 436--449.","DOI":"10.1109\/ICDE55515.2023.00040"},{"key":"e_1_2_1_10_1","volume-title":"Tung","author":"Huang Qiang","year":"2024","unstructured":"Qiang Huang, Yanhao Wang, Yiqun Sun, and Anthony K. H. Tung. 2024. Diversity-Aware k-Maximum Inner Product Search Revisited. arXiv:2402.13858"},{"key":"e_1_2_1_11_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence 37","author":"Huang Qiang","year":"2023","unstructured":"Qiang Huang, Yanhao Wang, and Anthony K. H. Tung. 2023. SAH: Shifting-Aware Asymmetric Hashing for Reverse k Maximum Inner Product Search. Proceedings of the AAAI Conference on Artificial Intelligence 37, 4 (2023), 4312--4321."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.psych.60.110707.163600"},{"key":"e_1_2_1_13_1","unstructured":"Xianming Li and Jing Li. 2023. Angle-optimized text embeddings. arXiv:2309.12871"},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Nils Reimers and Iryna Gurevych. 2019. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In EMNLP. 3982--3992.","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_2_1_15_1","unstructured":"Hugo Touvron Louis Martin et al. 2023. 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