{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T15:04:23Z","timestamp":1769526263570,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":33,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,7,6]]},"DOI":"10.1145\/3477495.3531839","type":"proceedings-article","created":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T15:12:13Z","timestamp":1657206733000},"page":"2249-2254","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Item Similarity Mining for Multi-Market Recommendation"],"prefix":"10.1145","author":[{"given":"Jiangxia","family":"Cao","sequence":"first","affiliation":[{"name":"Institute of Information Engineering, CAS & UCAS, Beijing, China"}]},{"given":"Xin","family":"Cong","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, CAS & UCAS, Beijing, China"}]},{"given":"Tingwen","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, CAS & UCAS, Beijing, China"}]},{"given":"Bin","family":"Wang","sequence":"additional","affiliation":[{"name":"Xiaomi AI Lab, Xiaomi Inc., Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2022,7,7]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2016.7738886"},{"key":"e_1_3_2_2_2_1","volume-title":"Multi-stage Ensemble Model for Cross-market Recommendation. ArXiv","author":"Bernardis Cesare","year":"2022","unstructured":"Cesare Bernardis . 2022. Multi-stage Ensemble Model for Cross-market Recommendation. ArXiv ( 2022 ). Cesare Bernardis. 2022. Multi-stage Ensemble Model for Cross-market Recommendation. ArXiv (2022)."},{"key":"e_1_3_2_2_3_1","volume-title":"Cross-Market Product Recommendation. In ACM International Conference on Information and Knowledge Management (CIKM) .","author":"Bonab Hamed","year":"2021","unstructured":"Hamed Bonab , Mohammad Aliannejadi , Ali Vardasbi , Evangelos Kanoulas , and James Allan . 2021 . Cross-Market Product Recommendation. In ACM International Conference on Information and Knowledge Management (CIKM) . Hamed Bonab, Mohammad Aliannejadi, Ali Vardasbi, Evangelos Kanoulas, and James Allan. 2021. Cross-Market Product Recommendation. In ACM International Conference on Information and Knowledge Management (CIKM) ."},{"key":"e_1_3_2_2_4_1","volume-title":"Deep Structural Point Process for Learning Temporal Interaction Networks. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML\/PKDD) .","author":"Cao Jiangxia","year":"2021","unstructured":"Jiangxia Cao , Xixun Lin , Xin Cong , Shu Guo , Hengzhu Tang , Tingwen Liu , and Bin Wang . 2021 a . Deep Structural Point Process for Learning Temporal Interaction Networks. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML\/PKDD) . Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo, Hengzhu Tang, Tingwen Liu, and Bin Wang. 2021 a. Deep Structural Point Process for Learning Temporal Interaction Networks. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML\/PKDD) ."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441783"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00211"},{"key":"e_1_3_2_2_7_1","volume-title":"WSDM Cup Workshop .","author":"Chen Zeyuan","year":"2022","unstructured":"Zeyuan Chen , He Wang , Xiangyu Zhu , Haiyan Wu , Congcong Gu , Shumeng Liu , Jinchao Huang , and Wei Zhang . 2022 . A Practical Two-stage Ranking Framework for Cross-market Recommendation . In WSDM Cup Workshop . Zeyuan Chen, He Wang, Xiangyu Zhu, Haiyan Wu, Congcong Gu, Shumeng Liu, Jinchao Huang, and Wei Zhang. 2022. A Practical Two-stage Ranking Framework for Cross-market Recommendation. In WSDM Cup Workshop ."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450005"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498464"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-06605-9_4"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"crossref","unstructured":"Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable feature learning for networks. In ACM Knowledge Discovery and Data Mining (KDD) .  Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable feature learning for networks. In ACM Knowledge Discovery and Data Mining (KDD) .","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_13_1","volume-title":"Neural Collaborative Filtering. In The World Wide Web Conference (WWW) .","author":"He Xiangnan","year":"2017","unstructured":"Xiangnan He , Lizi Liao , Hanwang Zhang , Liqiang Nie , Xia Hu , and Tat-Seng Chua . 2017 . Neural Collaborative Filtering. In The World Wide Web Conference (WWW) . Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017. Neural Collaborative Filtering. In The World Wide Web Conference (WWW) ."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"crossref","unstructured":"Zexi Huang Arlei Silva and Ambuj Singh. 2021. A Broader Picture of Random-walk Based Graph Embedding. In ACM Knowledge Discovery and Data Mining (KDD) .  Zexi Huang Arlei Silva and Ambuj Singh. 2021. A Broader Picture of Random-walk Based Graph Embedding. In ACM Knowledge Discovery and Data Mining (KDD) .","DOI":"10.1145\/3447548.3467300"},{"key":"e_1_3_2_2_15_1","volume-title":"Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS)","author":"Jaana Kalervo","year":"2002","unstructured":"Kalervo J\"arvelin and Jaana Kek\"al\"ainen. 2002. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS) ( 2002 ). Kalervo J\"arvelin and Jaana Kek\"al\"ainen. 2002. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS) (2002)."},{"key":"e_1_3_2_2_16_1","volume-title":"Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR) .","author":"Diederik Kingma P.","year":"2015","unstructured":"P. Diederik Kingma and Lei Jimmy Ba . 2015 . Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR) . P. Diederik Kingma and Lei Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR) ."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Walid Krichene and Steffen Rendle. 2020. On sampled metrics for item recommendation. In ACM Knowledge Discovery and Data Mining (KDD) .  Walid Krichene and Steffen Rendle. 2020. On sampled metrics for item recommendation. In ACM Knowledge Discovery and Data Mining (KDD) .","DOI":"10.1145\/3394486.3403226"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412012"},{"key":"e_1_3_2_2_19_1","volume-title":"H Chi","author":"Ma Jiaqi","year":"2018","unstructured":"Jiaqi Ma , Zhe Zhao , Xinyang Yi , Jilin Chen , Lichan Hong , and Ed H Chi . 2018 . Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. In ACM Knowledge Discovery and Data Mining (KDD) . Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, and Ed H Chi. 2018. Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. In ACM Knowledge Discovery and Data Mining (KDD) ."},{"key":"e_1_3_2_2_20_1","volume-title":"Annual Conference on Neural Information Processing Systems (NeurIPS) .","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov , Kai Chen , Greg Corrado , and Jeffrey Dean . 2013 . Efficient estimation of word representations in vector space . In Annual Conference on Neural Information Processing Systems (NeurIPS) . Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. In Annual Conference on Neural Information Processing Systems (NeurIPS) ."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.433"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2011.134"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366424.3384362"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481941"},{"key":"e_1_3_2_2_26_1","volume-title":"Two decades of recommender systems at Amazon. com","author":"Smith Brent","year":"2017","unstructured":"Brent Smith and Greg Linden . 2017. Two decades of recommender systems at Amazon. com . IEEE International Computing ( 2017 ). Brent Smith and Greg Linden. 2017. Two decades of recommender systems at Amazon. com. IEEE International Computing (2017)."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313710"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371774"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474273"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.6028\/NIST.SP.500-242"},{"key":"e_1_3_2_2_32_1","volume-title":"WSDM Cup Workshop .","author":"Zhang Peng","year":"2022","unstructured":"Peng Zhang , Rongxiu Gao , Changyv Li , Baoyin Liu , and Sheng Zhou . 2022 a. A Learning to Rank method for Cross-market Recommendation . In WSDM Cup Workshop . Peng Zhang, Rongxiu Gao, Changyv Li, Baoyin Liu, and Sheng Zhou. 2022 a. A Learning to Rank method for Cross-market Recommendation. In WSDM Cup Workshop ."},{"key":"e_1_3_2_2_33_1","volume-title":"An Effective Way for Cross-Market Recommendation with Hybrid Pre-Ranking and Ranking Models. In WSDM Cup Workshop .","author":"Zhang Qi","year":"2022","unstructured":"Qi Zhang , Zijian Yang , Yilun Huang , Jiarong He , and Lixiang Wang . 2022 b . An Effective Way for Cross-Market Recommendation with Hybrid Pre-Ranking and Ranking Models. In WSDM Cup Workshop . Qi Zhang, Zijian Yang, Yilun Huang, Jiarong He, and Lixiang Wang. 2022 b. An Effective Way for Cross-Market Recommendation with Hybrid Pre-Ranking and Ranking Models. In WSDM Cup Workshop ."}],"event":{"name":"SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Madrid Spain","acronym":"SIGIR '22","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531839","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3477495.3531839","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:26Z","timestamp":1750183826000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,6]]},"references-count":33,"alternative-id":["10.1145\/3477495.3531839","10.1145\/3477495"],"URL":"https:\/\/doi.org\/10.1145\/3477495.3531839","relation":{},"subject":[],"published":{"date-parts":[[2022,7,6]]},"assertion":[{"value":"2022-07-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}