{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T10:00:49Z","timestamp":1766138449350,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,14]],"date-time":"2023-09-14T00:00:00Z","timestamp":1694649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,14]]},"DOI":"10.1145\/3604915.3608804","type":"proceedings-article","created":{"date-parts":[[2023,9,14]],"date-time":"2023-09-14T22:40:23Z","timestamp":1694731223000},"page":"576-587","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["KGTORe: Tailored Recommendations through Knowledge-aware GNN Models"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8027-9475","authenticated-orcid":false,"given":"Alberto Carlo Maria","family":"Mancino","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy and Dipartimento di Ingegneria Informatica, Automatica E Gestionale - Antonio Ruberti, Universit\u00e0 degli Studi di Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1921-8304","authenticated-orcid":false,"given":"Antonio","family":"Ferrara","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6979-1715","authenticated-orcid":false,"given":"Salvatore","family":"Bufi","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2228-0333","authenticated-orcid":false,"given":"Daniele","family":"Malitesta","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0939-5462","authenticated-orcid":false,"given":"Tommaso","family":"Di Noia","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5484-9945","authenticated-orcid":false,"given":"Eugenio","family":"Di Sciascio","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Italy"}]}],"member":"320","published-online":{"date-parts":[[2023,9,14]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). In RecSys. ACM, 663\u2013666","author":"Anelli Vito\u00a0Walter","year":"2022","unstructured":"Vito\u00a0Walter Anelli, Pierpaolo Basile, Gerard de Melo, Francesco\u00a0Maria Donini, Antonio Ferrara, Cataldo Musto, Fedelucio Narducci, Azzurra Ragone, and Markus Zanker. 2022. Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). In RecSys. ACM, 663\u2013666."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Vito\u00a0Walter Anelli Luca Belli Yashar Deldjoo Tommaso\u00a0Di Noia Antonio Ferrara Fedelucio Narducci and Claudio Pomo. 2021. Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications. In RecSys. ACM 838\u2013841.","DOI":"10.1145\/3460231.3473326"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Vito\u00a0Walter Anelli Yashar Deldjoo Tommaso\u00a0Di Noia Daniele Malitesta and Felice\u00a0Antonio Merra. 2021. A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. In SIGIR. ACM 1094\u20131103.","DOI":"10.1145\/3404835.3462848"},{"key":"e_1_3_2_1_4_1","unstructured":"Vito\u00a0Walter Anelli Yashar Deldjoo Tommaso\u00a0Di Noia Eugenio\u00a0Di Sciascio Antonio Ferrara Daniele Malitesta and Claudio Pomo. 2022. Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews. In DL4SR@CIKM(CEUR Workshop Proceedings Vol.\u00a03317). CEUR-WS.org."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Vito\u00a0Walter Anelli Tommaso\u00a0Di Noia Eugenio\u00a0Di Sciascio Antonio Ferrara and Alberto Carlo\u00a0Maria Mancino. 2021. Sparse Feature Factorization for Recommender Systems with Knowledge Graphs. In RecSys. ACM 154\u2013165.","DOI":"10.1145\/3460231.3474243"},{"volume-title":"ISWC (1)(Lecture Notes in Computer Science, Vol.\u00a011778)","author":"Anelli Vito\u00a0Walter","key":"e_1_3_2_1_6_1","unstructured":"Vito\u00a0Walter Anelli, Tommaso\u00a0Di Noia, Eugenio\u00a0Di Sciascio, Azzurra Ragone, and Joseph Trotta. 2019. How to Make Latent Factors Interpretable by Feeding Factorization Machines with Knowledge Graphs. In ISWC (1)(Lecture Notes in Computer Science, Vol.\u00a011778). Springer, 38\u201356."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3010215"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Lars Backstrom and Jure Leskovec. 2011. Supervised random walks: predicting and recommending links in social networks. In WSDM. ACM 635\u2013644.","DOI":"10.1145\/1935826.1935914"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2011.07.021"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Peter Brusilovsky Alfred Kobsa and Wolfgang Nejdl (Eds.). 2007. The Adaptive Web Methods and Strategies of Web Personalization. Lecture Notes in Computer Science Vol.\u00a04321. Springer.","DOI":"10.1007\/978-3-540-72079-9"},{"volume-title":"Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach","author":"Chen Lei","key":"e_1_3_2_1_11_1","unstructured":"Lei Chen, Le Wu, Richang Hong, Kun Zhang, and Meng Wang. 2020. Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI. AAAI Press, 27\u201334."},{"volume-title":"Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation","author":"Chen Yankai","key":"e_1_3_2_1_12_1","unstructured":"Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, and Irwin King. 2022. Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation. In ICDE. IEEE, 299\u2013311."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2021.3129958"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Paul Covington Jay Adams and Emre Sargin. 2016. Deep Neural Networks for YouTube Recommendations. In RecSys. ACM 191\u2013198.","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531987"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Travis Ebesu Bin Shen and Yi Fang. 2018. Collaborative Memory Network for Recommendation Systems. In SIGIR. ACM 515\u2013524.","DOI":"10.1145\/3209978.3209991"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3588901"},{"key":"e_1_3_2_1_18_1","volume-title":"AISTATS(JMLR Proceedings, Vol.\u00a09). JMLR.org, 249\u2013256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In AISTATS(JMLR Proceedings, Vol.\u00a09). JMLR.org, 249\u2013256."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Nadav Golbandi Yehuda Koren and Ronny Lempel. 2011. Adaptive bootstrapping of recommender systems using decision trees. In WSDM. ACM 595\u2013604.","DOI":"10.1145\/1935826.1935910"},{"volume-title":"Recommender Systems Handbook","author":"Gunawardana Asela","key":"e_1_3_2_1_20_1","unstructured":"Asela Gunawardana and Guy Shani. 2015. Evaluating Recommender Systems. In Recommender Systems Handbook. Springer, 265\u2013308."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Xiangnan He Kuan Deng Xiang Wang Yan Li Yong-Dong Zhang and Meng Wang. 2020. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. In SIGIR. ACM 639\u2013648.","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural Collaborative Filtering. In WWW. ACM 173\u2013182.","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Ruoran Huang Chuanqi Han and Li Cui. 2021. Entity-aware Collaborative Relation Network with Knowledge Graph for Recommendation. In CIKM. ACM 3098\u20133102.","DOI":"10.1145\/3459637.3482098"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Dietmar Jannach Michael Jugovac and Ingrid Nunes. 2019. Explanations and User Control in Recommender Systems. In ABIS@HT. ACM 31.","DOI":"10.1145\/3345002.3349293"},{"key":"e_1_3_2_1_25_1","series-title":"Lecture Notes in Computer Science, Vol.\u00a010100","volume-title":"Social Information Access","author":"Jannach Dietmar","unstructured":"Dietmar Jannach, Lukas Lerche, and Markus Zanker. 2018. Recommending Based on Implicit Feedback. In Social Information Access. Lecture Notes in Computer Science, Vol.\u00a010100. Springer, 510\u2013569."},{"key":"e_1_3_2_1_26_1","volume-title":"Kipf and Max Welling","author":"N.","year":"2017","unstructured":"Thomas\u00a0N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR (Poster). OpenReview.net."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1644873.1644874"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Walid Krichene and Steffen Rendle. 2020. On Sampled Metrics for Item Recommendation. In KDD. ACM 1748\u20131757.","DOI":"10.1145\/3394486.3403226"},{"volume-title":"WISA(Lecture Notes in Computer Science, Vol.\u00a012432)","author":"Li Jian","key":"e_1_3_2_1_29_1","unstructured":"Jian Li, Zhuoming Xu, Yan Tang, Bo Zhao, and Haimei Tian. 2020. Deep Hybrid Knowledge Graph Embedding for Top-N Recommendation. In WISA(Lecture Notes in Computer Science, Vol.\u00a012432). Springer, 59\u201370."},{"key":"e_1_3_2_1_30_1","unstructured":"Kelong Mao Jieming Zhu Xi Xiao Biao Lu Zhaowei Wang and Xiuqiang He. 2021. UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. In CIKM. ACM 1253\u20131262."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Xia Ning and George Karypis. 2012. Sparse linear methods with side information for top-n recommendations. In RecSys. ACM 155\u2013162.","DOI":"10.1145\/2365952.2365983"},{"volume-title":"Factorization Machines","author":"Rendle Steffen","key":"e_1_3_2_1_32_1","unstructured":"Steffen Rendle. 2010. Factorization Machines. In ICDM. IEEE Computer Society, 995\u20131000."},{"key":"e_1_3_2_1_33_1","volume-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. AUAI Press, 452\u2013461."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Yifei Shen Yongji Wu Yao Zhang Caihua Shan Jun Zhang Khaled\u00a0B. Letaief and Dongsheng Li. 2021. How Powerful is Graph Convolution for Recommendation?. In CIKM. ACM 1619\u20131629.","DOI":"10.1145\/3459637.3482264"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Jie Shuai Kun Zhang Le Wu Peijie Sun Richang Hong Meng Wang and Yong Li. 2022. A Review-aware Graph Contrastive Learning Framework for Recommendation. In SIGIR. ACM 1283\u20131293.","DOI":"10.1145\/3477495.3531927"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Giuseppe Spillo Cataldo Musto Marco de Gemmis Pasquale Lops and Giovanni Semeraro. 2022. Exploiting Neuro-Symbolic Graph Embeddings based on First-Order Logical Rules for Knowledge-aware Recommendations. In DP@AI*IA(CEUR Workshop Proceedings Vol.\u00a03419). CEUR-WS.org 1\u201311.","DOI":"10.1145\/3523227.3551484"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"Harald Steck. 2013. Evaluation of recommendations: rating-prediction and ranking. In RecSys. ACM 213\u2013220.","DOI":"10.1145\/2507157.2507160"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Changxin Tian Yuexiang Xie Yaliang Li Nan Yang and Wayne\u00a0Xin Zhao. 2022. Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering. In SIGIR. ACM 122\u2013132.","DOI":"10.1145\/3477495.3531889"},{"key":"e_1_3_2_1_39_1","volume-title":"Artificial Intelligence: Foundations, Applications and Challenges. Studies on the Semantic Web, Vol.\u00a047","author":"Tiddi Ilaria","year":"2020","unstructured":"Ilaria Tiddi, Freddy L\u00e9cu\u00e9, and Pascal Hitzler (Eds.). 2020. Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges. Studies on the Semantic Web, Vol.\u00a047. IOS Press."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Riku Togashi Mayu Otani and Shin\u2019ichi Satoh. 2021. Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph. In WSDM. ACM 931\u2013939.","DOI":"10.1145\/3437963.3441773"},{"key":"e_1_3_2_1_41_1","unstructured":"Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. In ICLR (Poster). OpenReview.net."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Fuzheng Zhang Jialin Wang Miao Zhao Wenjie Li Xing Xie and Minyi Guo. 2018. RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems. In CIKM. ACM 417\u2013426.","DOI":"10.1145\/3269206.3271739"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3312738"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Fuzheng Zhang Mengdi Zhang Jure Leskovec Miao Zhao Wenjie Li and Zhongyuan Wang. 2019. Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems. In KDD. ACM 968\u2013977.","DOI":"10.1145\/3292500.3330836"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Miao Zhao Xing Xie Wenjie Li and Minyi Guo. 2019. Knowledge Graph Convolutional Networks for Recommender Systems. In WWW. ACM 3307\u20133313.","DOI":"10.1145\/3308558.3313417"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019. Neural Graph Collaborative Filtering. In SIGIR. ACM 165\u2013174.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Tinglin Huang Dingxian Wang Yancheng Yuan Zhenguang Liu Xiangnan He and Tat-Seng Chua. 2021. Learning Intents behind Interactions with Knowledge Graph for Recommendation. In WWW. ACM \/ IW3C2 878\u2013887.","DOI":"10.1145\/3442381.3450133"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Hongye Jin An Zhang Xiangnan He Tong Xu and Tat-Seng Chua. 2020. Disentangled Graph Collaborative Filtering. In SIGIR. ACM 1001\u20131010.","DOI":"10.1145\/3397271.3401137"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401141"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"crossref","unstructured":"Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian and Xing Xie. 2021. Self-supervised Graph Learning for Recommendation. In SIGIR. ACM 726\u2013735.","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Yuhao Yang Chao Huang Lianghao Xia and Chenliang Li. 2022. Knowledge Graph Contrastive Learning for Recommendation. In SIGIR. ACM 1434\u20131443.","DOI":"10.1145\/3477495.3532009"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William\u00a0L. Hamilton and Jure Leskovec. 2018. Graph Convolutional Neural Networks for Web-Scale Recommender Systems. In KDD. ACM 974\u2013983.","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","unstructured":"Fajie Yuan Xiangnan He Alexandros Karatzoglou and Liguang Zhang. 2020. Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation. In SIGIR. ACM 1469\u20131478.","DOI":"10.1145\/3397271.3401156"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"Huan Zhao Quanming Yao Jianda Li Yangqiu Song and Dik\u00a0Lun Lee. 2017. Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. In KDD. ACM 635\u2013644.","DOI":"10.1145\/3097983.3098063"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.07.030"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"crossref","unstructured":"Ding Zou Wei Wei Xian-Ling Mao Ziyang Wang Minghui Qiu Feida Zhu and Xin Cao. 2022. Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System. In SIGIR. ACM 1358\u20131368.","DOI":"10.1145\/3477495.3532025"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"crossref","unstructured":"Ding Zou Wei Wei Ziyang Wang Xian-Ling Mao Feida Zhu Rui Fang and Dangyang Chen. 2022. Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning. In CIKM. ACM 2817\u20132826.","DOI":"10.1145\/3511808.3557358"}],"event":{"name":"RecSys '23: Seventeenth ACM Conference on Recommender Systems","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGAI ACM Special Interest Group on Artificial Intelligence","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval","SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGecom Special Interest Group on Economics and Computation"],"location":"Singapore Singapore","acronym":"RecSys '23"},"container-title":["Proceedings of the 17th ACM Conference on Recommender Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604915.3608804","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3604915.3608804","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:46:06Z","timestamp":1750178766000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604915.3608804"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,14]]},"references-count":58,"alternative-id":["10.1145\/3604915.3608804","10.1145\/3604915"],"URL":"https:\/\/doi.org\/10.1145\/3604915.3608804","relation":{},"subject":[],"published":{"date-parts":[[2023,9,14]]},"assertion":[{"value":"2023-09-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}