{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:08:32Z","timestamp":1764842912468,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031708923"},{"type":"electronic","value":"9783031708930"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-70893-0_27","type":"book-chapter","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T11:02:54Z","timestamp":1724929374000},"page":"335-340","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MIND Your Language: A Multilingual Dataset for\u00a0Cross-Lingual News Recommendation (Extended Abstract)"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7248-7503","authenticated-orcid":false,"given":"Andreea","family":"Iana","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1301-6314","authenticated-orcid":false,"given":"Goran","family":"Glava\u0161","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4386-8195","authenticated-orcid":false,"given":"Heiko","family":"Paulheim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","unstructured":"An, M., Wu, F., Wu, C., Zhang, K., Liu, Z., Xie, X.: Neural news recommendation with long-and short-term user representations. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 336\u2013345 (2019). https:\/\/doi.org\/10.18653\/v1\/P19-1033","DOI":"10.18653\/v1\/P19-1033"},{"key":"27_CR2","first-page":"1149","volume":"51","author":"JM Balkin","year":"2017","unstructured":"Balkin, J.M.: Free speech in the algorithmic society: big data, private governance, and new school speech regulation. UCDL Rev. 51, 1149 (2017)","journal-title":"UCDL Rev."},{"key":"27_CR3","doi-asserted-by":"publisher","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 8440\u20138451 (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.747","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"27_CR4","unstructured":"Conneau, A., Lample, G.: Cross-lingual language model pretraining. In: Proceedings of the 33rd International Conference on Neural Information Processing Systems, pp. 7059\u20137069 (2019). https:\/\/arxiv.org\/abs\/1901.07291"},{"key":"27_CR5","unstructured":"Costa-juss\u00e0, M.R., et\u00a0al.: No language left behind: Scaling human-centered machine translation. arXiv preprint arXiv:2207.04672 (2022)"},{"issue":"5","key":"27_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3406095","volume":"53","author":"R Dabre","year":"2020","unstructured":"Dabre, R., Chu, C., Kunchukuttan, A.: A survey of multilingual neural machine translation. ACM Comput. Surv. (CSUR) 53(5), 1\u201338 (2020). https:\/\/doi.org\/10.1145\/3406095","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"107","key":"27_CR7","first-page":"1","volume":"22","author":"A Fan","year":"2021","unstructured":"Fan, A., et al.: Beyond English-centric multilingual machine translation. J. Mach. Learn. Res. 22(107), 1\u201348 (2021)","journal-title":"J. Mach. Learn. Res."},{"key":"27_CR8","doi-asserted-by":"publisher","unstructured":"Gabriel De\u00a0Souza, P.M., Jannach, D., Da\u00a0Cunha, A.M.: Contextual hybrid session-based news recommendation with recurrent neural networks. IEEE Access 7, 169185\u2013169203 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2954957","DOI":"10.1109\/ACCESS.2019.2954957"},{"key":"27_CR9","doi-asserted-by":"publisher","unstructured":"Gulla, J.A., Zhang, L., Liu, P., \u00d6zg\u00f6bek, \u00d6., Su, X.: The Adressa dataset for news recommendation. In: Proceedings of the International Conference on Web Intelligence, pp. 1042\u20131048 (2017). https:\/\/doi.org\/10.1145\/3106426.3109436","DOI":"10.1145\/3106426.3109436"},{"issue":"3","key":"27_CR10","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1162\/coli_a_00446","volume":"48","author":"B Haddow","year":"2022","unstructured":"Haddow, B., Bawden, R., Barone, A.V.M., Helcl, J., Birch, A.: Survey of low-resource machine translation. Comput. Linguist. 48(3), 673\u2013732 (2022). https:\/\/doi.org\/10.1162\/coli_a_00446","journal-title":"Comput. Linguist."},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"Helberger, N.: On the democratic role of news recommenders. In: Algorithms, Automation, and News, pp. 14\u201333. Routledge (2021)","DOI":"10.4324\/9781003099260-2"},{"key":"27_CR12","unstructured":"Iana, A., et al.: Nemig-a bilingual news collection and knowledge graph about migration. In: Proceedings of the Workshop on News Recommendation and Analytics co-located with RecSys 2023 (2023)"},{"key":"27_CR13","doi-asserted-by":"publisher","unstructured":"Iana, A., Glava\u0161, G., Paulheim, H.: Newsreclib: a pytorch-lightning library for neural news recommendation. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 296\u2013310 (2023). https:\/\/doi.org\/10.18653\/v1\/2023.emnlp-demo.26","DOI":"10.18653\/v1\/2023.emnlp-demo.26"},{"key":"27_CR14","unstructured":"Iana, A., Glava\u0161, G., Paulheim, H.: Train once, use flexibly: a modular framework for multi-aspect neural news recommendation. arXiv preprint arXiv:2307.16089 (2023)"},{"key":"27_CR15","doi-asserted-by":"publisher","unstructured":"Iana, A., Glavas, G., Paulheim, H.: Mind your language: a multilingual dataset for cross-lingual news recommendation. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024). https:\/\/doi.org\/10.1145\/3626772.3657867","DOI":"10.1145\/3626772.3657867"},{"key":"27_CR16","doi-asserted-by":"publisher","unstructured":"Joshi, P., Santy, S., Budhiraja, A., Bali, K., Choudhury, M.: The state and fate of linguistic diversity and inclusion in the NLP world. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 6282\u20136293 (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.560","DOI":"10.18653\/v1\/2020.acl-main.560"},{"key":"27_CR17","doi-asserted-by":"publisher","unstructured":"Kille, B., Hopfgartner, F., Brodt, T., Heintz, T.: The plista dataset. In: Proceedings of the 2013 International News Recommender Systems Workshop and Challenge, pp. 16\u201323 (2013). https:\/\/doi.org\/10.1145\/2516641.2516643","DOI":"10.1145\/2516641.2516643"},{"key":"27_CR18","unstructured":"Kudugunta, S., et al.: Madlad-400: a multilingual and document-level large audited dataset. In: Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2023)"},{"key":"27_CR19","doi-asserted-by":"publisher","unstructured":"Li, J., et al.: Miner: multi-interest matching network for news recommendation. In: Findings of the Association for Computational Linguistics: ACL 2022, pp. 343\u2013352 (2022). https:\/\/doi.org\/10.18653\/v1\/2022.findings-acl.29","DOI":"10.18653\/v1\/2022.findings-acl.29"},{"issue":"6","key":"27_CR20","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1080\/10447318.2019.1662636","volume":"36","author":"C Ling","year":"2020","unstructured":"Ling, C., Steichen, B., Figueira, S.: Multilingual news-an investigation of consumption, querying, and search result selection behaviors. Int. J. Hum.-Comput. Interact. 36(6), 516\u2013535 (2020). https:\/\/doi.org\/10.1080\/10447318.2019.1662636","journal-title":"Int. J. Hum.-Comput. Interact."},{"key":"27_CR21","unstructured":"Lucas, J.P., da\u00a0Silva, J.F.G., Figueiredo, L.F.: NPR: a news portal recommendations dataset. In: Proceedings of the The First Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2023), co-located with the ACM Conference on Recommender Systems 2023 (RecSys 2023) (2023)"},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Pariser, E.: The filter bubble: what the Internet is hiding from you. Penguin UK (2011)","DOI":"10.3139\/9783446431164"},{"key":"27_CR23","doi-asserted-by":"publisher","unstructured":"Qi, T., Wu, F., Wu, C., Huang, Y.: News recommendation with candidate-aware user modeling. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1917\u20131921 (2022). https:\/\/doi.org\/10.1145\/3477495.3531778","DOI":"10.1145\/3477495.3531778"},{"key":"27_CR24","doi-asserted-by":"publisher","unstructured":"de\u00a0Souza Pereira\u00a0Moreira, G., Ferreira, F., da\u00a0Cunha, A.M.: News session-based recommendations using deep neural networks. In: Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems, pp. 15\u201323 (2018). https:\/\/doi.org\/10.1145\/3270323.3270328","DOI":"10.1145\/3270323.3270328"},{"key":"27_CR25","unstructured":"Touvron, H., et\u00a0al.: Llama: open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023). https:\/\/arxiv.org\/abs\/2302.13971"},{"key":"27_CR26","doi-asserted-by":"publisher","unstructured":"Wang, R., Wang, S., Lu, W., Peng, X.: News recommendation via multi-interest news sequence modelling. In: 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2022, pp. 7942\u20137946. IEEE (2022). https:\/\/doi.org\/10.1109\/ICASSP43922.2022.9747149","DOI":"10.1109\/ICASSP43922.2022.9747149"},{"key":"27_CR27","unstructured":"Wei, X., et\u00a0al.: Polylm: an open source polyglot large language model. arXiv preprint arXiv:2307.06018 (2023). https:\/\/arxiv.org\/abs\/2307.06018"},{"key":"27_CR28","unstructured":"Wei, X., Weng, R., Hu, Y., Xing, L., Yu, H., Luo, W.: On learning universal representations across languages. In: International Conference on Learning Representations (2020)"},{"key":"27_CR29","unstructured":"Workshop, B., et\u00a0al.: Bloom: a 176b-parameter open-access multilingual language model. arXiv preprint arXiv:2211.05100 (2022). https:\/\/arxiv.org\/abs\/2211.05100"},{"key":"27_CR30","doi-asserted-by":"publisher","unstructured":"Wu, C., Wu, F., An, M., Huang, J., Huang, Y., Xie, X.: Neural news recommendation with attentive multi-view learning. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp. 3863\u20133869 (2019). https:\/\/doi.org\/10.24963\/ijcai.2019\/536","DOI":"10.24963\/ijcai.2019\/536"},{"key":"27_CR31","doi-asserted-by":"publisher","unstructured":"Wu, C., Wu, F., An, M., Huang, Y., Xie, X.: Neural news recommendation with topic-aware news representation. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1154\u20131159 (2019). https:\/\/doi.org\/10.18653\/v1\/P19-1110","DOI":"10.18653\/v1\/P19-1110"},{"issue":"1","key":"27_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3530257","volume":"41","author":"C Wu","year":"2023","unstructured":"Wu, C., Wu, F., Huang, Y., Xie, X.: Personalized news recommendation: methods and challenges. ACM Trans. Inf. Syst. 41(1), 1\u201350 (2023). https:\/\/doi.org\/10.1145\/3530257","journal-title":"ACM Trans. Inf. Syst."},{"key":"27_CR33","doi-asserted-by":"publisher","unstructured":"Wu, C., Wu, F., Qi, T., Huang, Y.: Empowering news recommendation with pre-trained language models. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1652\u20131656 (2021). https:\/\/doi.org\/10.1145\/3404835.3463069","DOI":"10.1145\/3404835.3463069"},{"key":"27_CR34","doi-asserted-by":"publisher","unstructured":"Wu, F., et\u00a0al.: Mind: a large-scale dataset for news recommendation. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3597\u20133606 (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.331","DOI":"10.18653\/v1\/2020.acl-main.331"},{"key":"27_CR35","doi-asserted-by":"publisher","unstructured":"Xue, L., et al.: mt5: a massively multilingual pre-trained text-to-text transformer. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 483\u2013498 (2021). https:\/\/doi.org\/10.18653\/v1\/2021.naacl-main.41","DOI":"10.18653\/v1\/2021.naacl-main.41"},{"key":"27_CR36","unstructured":"Zuckerman, E.: The polyglot internet (2008). https:\/\/ethanzuckerman.com\/the-polyglot-internet\/"}],"container-title":["Lecture Notes in Computer Science","KI 2024: Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70893-0_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T11:08:29Z","timestamp":1724929709000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70893-0_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031708923","9783031708930"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70893-0_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"30 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"German Conference on Artificial Intelligence (K\u00fcnstliche Intelligenz)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"W\u00fcrzburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"47","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ki2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.informatik.uni-wuerzburg.de\/ki24\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}