{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:51:30Z","timestamp":1777614690352,"version":"3.51.4"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032061058","type":"print"},{"value":"9783032061065","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-06106-5_1","type":"book-chapter","created":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T10:08:59Z","timestamp":1759399739000},"page":"3-20","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Counterfactual Multi-player Bandits for\u00a0Explainable Recommendation Diversification"],"prefix":"10.1007","author":[{"given":"Yansen","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bowei","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaokun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haolun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zexu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,3]]},"reference":[{"key":"1_CR1","unstructured":"Bistritz, I., Bambos, N.: Cooperative multi-player bandit optimization. In: NeurIPS, pp. 2016\u20132027 (2020)"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Bubeck, S., Munos, R., Stoltz, G.: Pure exploration in multi-armed bandits problems. In: International Conference on Algorithmic Learning Theory, pp. 23\u201337 (2009)","DOI":"10.1007\/978-3-642-04414-4_7"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: SIGIR, pp. 335\u2013336 (1998)","DOI":"10.1145\/290941.291025"},{"key":"1_CR4","unstructured":"Chen, L., Zhang, G., Zhou, E.: Fast greedy MAP inference for determinantal point process to improve recommendation diversity. In: NeurIPS, pp. 5627\u20135638 (2018)"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Chen, W., Ren, P., Cai, F., Sun, F., de\u00a0Rijke, M.: Improving end-to-end sequential recommendations with intent-aware diversification. In: CIKM, pp. 175\u2013184 (2020)","DOI":"10.1145\/3340531.3411897"},{"key":"1_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Z., Silvestri, F., Wang, J., Zhu, H., Ahn, H., Tolomei, G.: Relax: reinforcement learning agent explainer for arbitrary predictive models. In: CIKM, pp. 252\u2013261 (2022)","DOI":"10.1145\/3511808.3557429"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Cheng, P., Wang, S., Ma, J., Sun, J., Xiong, H.: Learning to recommend accurate and diverse items. In: WWW, pp. 183\u2013192 (2017)","DOI":"10.1145\/3038912.3052585"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Clarke, C.L., et al.: Novelty and diversity in information retrieval evaluation. In: SIGIR, pp. 659\u2013666 (2008)","DOI":"10.1145\/1390334.1390446"},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Ding, Q., Liu, Y., Miao, C., Cheng, F., Tang, H.: A hybrid bandit framework for diversified recommendation. In: AAAI, pp. 4036\u20134044 (2021)","DOI":"10.1609\/aaai.v35i5.16524"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Ge, M., Delgado-Battenfeld, C., Jannach, D.: Beyond accuracy: evaluating recommender systems by coverage and serendipity. In: RecSys, pp. 257\u2013260 (2010)","DOI":"10.1145\/1864708.1864761"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Ge, Y., et al.: Explainable fairness in recommendation. In: SIGIR, pp. 681\u2013691 (2022)","DOI":"10.1145\/3477495.3531973"},{"issue":"4","key":"1_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2827872","volume":"5","author":"FM Harper","year":"2015","unstructured":"Harper, F.M., Konstan, J.A.: The movielens datasets: History and context. TIIS 5(4), 1\u201319 (2015)","journal-title":"TIIS"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"He, X., Deng, K., Wang, X., Li, Y., Zhang, Y., Wang, M.: Lightgcn: simplifying and powering graph convolution network for recommendation. In: SIGIR, pp. 639\u2013648 (2020)","DOI":"10.1145\/3397271.3401063"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Huang, Y., Wang, W., Zhang, L., Xu, R.: Sliding spectrum decomposition for diversified recommendation. In: KDD, pp. 3041\u20133049 (2021)","DOI":"10.1145\/3447548.3467108"},{"key":"1_CR15","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Li, L., Chu, W., Langford, J., Schapire, R.E.: A contextual-bandit approach to personalized news article recommendation. In: WWW, pp. 661\u2013670 (2010)","DOI":"10.1145\/1772690.1772758"},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Li, S., Zhou, Y., Zhang, D., Zhang, Y., Lan, X.: Learning to diversify recommendations based on matrix factorization. In: DASC\/PiCom\/DataCom\/CyberSciTech. pp. 68\u201374 (2017)","DOI":"10.1109\/DASC-PICom-DataCom-CyberSciTec.2017.26"},{"issue":"3810","key":"1_CR18","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1126\/science.159.3810.56","volume":"159","author":"RK Merton","year":"1968","unstructured":"Merton, R.K.: The matthew effect in science: the reward and communication systems of science are considered. Science 159(3810), 56\u201363 (1968)","journal-title":"Science"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Ni, J., Li, J., McAuley, J.J.: Justifying recommendations using distantly-labeled reviews and fine-grained aspects. In: EMNLP-IJCNLP, pp. 188\u2013197 (2019)","DOI":"10.18653\/v1\/D19-1018"},{"key":"1_CR20","unstructured":"Pariser, E.: The filter bubble: How the new personalized web is changing what we read and how we think (2011)"},{"key":"1_CR21","unstructured":"Rendle, S., Freudenthaler, C., Gantner, Z., Schmidt-Thieme, L.: BPR: bayesian personalized ranking from implicit feedback. In: UAI, pp. 452\u2013461 (2009)"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Santos, R.L., Macdonald, C., Ounis, I.: Exploiting query reformulations for web search result diversification. In: WWW, pp. 881\u2013890 (2010)","DOI":"10.1145\/1772690.1772780"},{"issue":"2","key":"1_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3618107","volume":"42","author":"X Shi","year":"2023","unstructured":"Shi, X., et al.: Relieving popularity bias in interactive recommendation: a diversity-novelty-aware reinforcement learning approach. TOIS 42(2), 1\u201330 (2023)","journal-title":"TOIS"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Singh, J., Anand, A.: Exs: Explainable search using local model agnostic interpretability. In: WSDM, pp. 770\u2013773 (2019)","DOI":"10.1145\/3289600.3290620"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Slivkins, A., et\u00a0al.: Introduction to multi-armed bandits. Found. Trends\u00ae Mach. Learn. 12(1-2), 1\u2013286 (2019)","DOI":"10.1561\/2200000068"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Tsukuda, K., Goto, M.: Dualdiv: diversifying items and explanation styles in explainable hybrid recommendation. In: RecSys, pp. 398\u2013402 (2019)","DOI":"10.1145\/3298689.3347063"},{"key":"1_CR27","doi-asserted-by":"crossref","unstructured":"Vargas, S., Castells, P., Vallet, D.: Intent-oriented diversity in recommender systems. In: SIGIR, pp. 1211\u20131212 (2011)","DOI":"10.1145\/2009916.2010124"},{"key":"1_CR28","doi-asserted-by":"crossref","unstructured":"Wang, X., Chen, Y., Yang, J., Wu, L., Wu, Z., Xie, X.: A reinforcement learning framework for explainable recommendation. In: ICDM, pp. 587\u2013596 (2018)","DOI":"10.1109\/ICDM.2018.00074"},{"key":"1_CR29","unstructured":"Wasilewski, J., Hurley, N.: Incorporating diversity in a learning to rank recommender system. In: FLAIRS, pp. 572\u2013578 (2016)"},{"key":"1_CR30","doi-asserted-by":"crossref","unstructured":"Wilhelm, M., Ramanathan, A., Bonomo, A., Jain, S., Chi, E.H., Gillenwater, J.: Practical diversified recommendations on youtube with determinantal point processes. In: CIKM, pp. 2165\u20132173 (2018)","DOI":"10.1145\/3269206.3272018"},{"key":"1_CR31","doi-asserted-by":"crossref","unstructured":"Wu, H., et al.: Result diversification in search and recommendation: a survey. In: TKDE (2024)","DOI":"10.1109\/TKDE.2024.3382262"},{"issue":"2","key":"1_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3298988","volume":"37","author":"L Wu","year":"2019","unstructured":"Wu, L., Quan, C., Li, C., Wang, Q., Zheng, B., Luo, X.: A context-aware user-item representation learning for item recommendation. TOIS 37(2), 1\u201329 (2019)","journal-title":"TOIS"},{"key":"1_CR33","doi-asserted-by":"crossref","unstructured":"Yu, H.: Optimize what you evaluate with: Search result diversification based on metric optimization. In: AAAI, pp. 10399\u201310407 (2022)","DOI":"10.1609\/aaai.v36i9.21282"},{"key":"1_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, M., Hurley, N.: Avoiding monotony: improving the diversity of recommendation lists. In: RecSys, pp. 123\u2013130 (2008)","DOI":"10.1145\/1454008.1454030"},{"key":"1_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Hu, C., Dai, G., Kong, W., Liu, Y.: Self-adaptive graph neural networks for personalized sequential recommendation. In: ICONIP, pp. 608\u2013619 (2021)","DOI":"10.1007\/978-3-030-92270-2_52"},{"key":"1_CR36","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, X., Cui, Z., Ma, C.: Shapley value-driven data pruning for recommender systems. In: KDD (2025)","DOI":"10.1145\/3711896.3737127"},{"key":"1_CR37","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Chen, X., et\u00a0al.: Explainable recommendation: A survey and new perspectives. Found. Trends\u00ae Inform. Retrieval 14(1), 1\u2013101 (2020)","DOI":"10.1561\/1500000066"},{"key":"1_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Lai, G., Zhang, M., Zhang, Y., Liu, Y., Ma, S.: Explicit factor models for explainable recommendation based on phrase-level sentiment analysis. In: SIGIR, pp. 83\u201392 (2014)","DOI":"10.1145\/2600428.2609579"},{"key":"1_CR39","doi-asserted-by":"crossref","unstructured":"Zheng, G., et al.: DRN: a deep reinforcement learning framework for news recommendation. In: WWW, pp. 167\u2013176 (2018)","DOI":"10.1145\/3178876.3185994"},{"key":"1_CR40","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Gao, C., Chen, L., Jin, D., Li, Y.: DGCN: Diversified recommendation with graph convolutional networks. In: WWW, pp. 401\u2013412 (2021)","DOI":"10.1145\/3442381.3449835"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Research Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06106-5_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T10:09:19Z","timestamp":1759399759000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06106-5_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,3]]},"ISBN":["9783032061058","9783032061065"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06106-5_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,3]]},"assertion":[{"value":"3 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecmlpkdd.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}