{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T17:30:05Z","timestamp":1772386205841,"version":"3.50.1"},"reference-count":67,"publisher":"Elsevier BV","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.elsevier.com\/tdm\/userlicense\/1.0\/"},{"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.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1016\/j.eswa.2023.121278","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T15:49:16Z","timestamp":1692805756000},"page":"121278","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":30,"special_numbering":"C","title":["MMKDGAT: Multi-modal Knowledge graph-aware Deep Graph Attention Network for remote sensing image recommendation"],"prefix":"10.1016","volume":"235","author":[{"given":"Fei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Xianzhang","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Cheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9845-4251","authenticated-orcid":false,"given":"Yongjun","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8203-1246","authenticated-orcid":false,"given":"Yansheng","family":"Li","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2023.121278_b1","doi-asserted-by":"crossref","DOI":"10.1155\/2014\/408492","article-title":"The representation of circular arc by using rational cubic timmer curve","volume":"2014","author":"Abbas","year":"2014","journal-title":"Mathematical Problems in Engineering"},{"issue":"20","key":"10.1016\/j.eswa.2023.121278_b2","doi-asserted-by":"crossref","first-page":"10183","DOI":"10.1016\/j.amc.2013.03.110","article-title":"The G2 and C2 rational quadratic trigonometric B\u00e9zier curve with two shape parameters with applications","volume":"219","author":"Bashir","year":"2013","journal-title":"Applied Mathematics and Computation"},{"key":"10.1016\/j.eswa.2023.121278_b3","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2014.03.009","article-title":"Who launched what, when and why; trends in global land-cover observation capacity from civilian earth observation satellites","volume":"103","author":"Belward","year":"2015","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"key":"10.1016\/j.eswa.2023.121278_b4","doi-asserted-by":"crossref","first-page":"165779","DOI":"10.1109\/ACCESS.2019.2953496","article-title":"A novel approach of hybrid trigonometric B\u00e9zier curve to the modeling of symmetric revolutionary curves and symmetric rotation surfaces","volume":"7","author":"BiBi","year":"2019","journal-title":"IEEE Access"},{"issue":"6","key":"10.1016\/j.eswa.2023.121278_b5","doi-asserted-by":"crossref","first-page":"967","DOI":"10.3390\/math8060967","article-title":"Geometric modeling of novel generalized hybrid trigonometric B\u00e9zier-like curve with shape parameters and its applications","volume":"8","author":"BiBi","year":"2020","journal-title":"Mathematics"},{"key":"10.1016\/j.eswa.2023.121278_b6","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., & Yakhnenko, O. (2013). Translating embeddings for modeling multi-relational data. In Neural information processing systems (pp. 1\u20139)."},{"key":"10.1016\/j.eswa.2023.121278_b7","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2021.104935","article-title":"Remote sensing image recommendation based on spatial\u2013temporal embedding topic model","volume":"157","author":"Chen","year":"2021","journal-title":"Computers & Geosciences"},{"key":"10.1016\/j.eswa.2023.121278_b8","series-title":"International conference on machine learning","first-page":"1725","article-title":"Simple and deep graph convolutional networks","author":"Chen","year":"2020"},{"key":"10.1016\/j.eswa.2023.121278_b9","first-page":"370","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Chen","year":"2019","journal-title":"Scientific Bulletin"},{"issue":"11","key":"10.1016\/j.eswa.2023.121278_b10","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/JPROC.2016.2598228","article-title":"Big data for remote sensing: Challenges and opportunities","volume":"104","author":"Chi","year":"2016","journal-title":"Proceedings of the IEEE"},{"key":"10.1016\/j.eswa.2023.121278_b11","doi-asserted-by":"crossref","unstructured":"Covington, P., Adams, J., & Sargin, E. (2016). Deep neural networks for youtube recommendations. In Proceedings of the 10th ACM conference on recommender systems (pp. 191\u2013198).","DOI":"10.1145\/2959100.2959190"},{"key":"10.1016\/j.eswa.2023.121278_b12","series-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"Glorot","year":"2010"},{"key":"10.1016\/j.eswa.2023.121278_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2020.112103","article-title":"Evaluation of machine learning algorithms for forest stand species mapping using sentinel-2 imagery and environmental data in the Polish Carpathians","volume":"251","author":"Grabska","year":"2020","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/j.eswa.2023.121278_b14","article-title":"A survey on knowledge graph-based recommender systems","author":"Guo","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2023.121278_b15","doi-asserted-by":"crossref","unstructured":"He, X., Deng, K., Wang, X., Li, Y., Zhang, Y., & Wang, M. (2020). Lightgcn: Simplifying and powering graph convolution network for recommendation. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval (pp. 639\u2013648).","DOI":"10.1145\/3397271.3401063"},{"key":"10.1016\/j.eswa.2023.121278_b16","doi-asserted-by":"crossref","unstructured":"He, R., & McAuley, J. (2016). VBPR: visual bayesian personalized ranking from implicit feedback. In Proceedings of the AAAI conference on artificial intelligence, vol. 30, no. 1.","DOI":"10.1609\/aaai.v30i1.9973"},{"key":"10.1016\/j.eswa.2023.121278_b17","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770\u2013778).","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.eswa.2023.121278_b18","doi-asserted-by":"crossref","unstructured":"Kampffmeyer, M., Salberg, A. B., & Jenssen, R. (2016). Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition workshops (pp. 1\u20139).","DOI":"10.1109\/CVPRW.2016.90"},{"key":"10.1016\/j.eswa.2023.121278_b19","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"10.1016\/j.eswa.2023.121278_b20","series-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"issue":"8","key":"10.1016\/j.eswa.2023.121278_b21","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MC.2009.263","article-title":"Matrix factorization techniques for recommender systems","volume":"42","author":"Koren","year":"2009","journal-title":"Computer"},{"key":"10.1016\/j.eswa.2023.121278_b22","doi-asserted-by":"crossref","unstructured":"Lei, C., Liu, D., Li, W., Zha, Z. J., & Li, H. (2016). Comparative deep learning of hybrid representations for image recommendations. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2545\u20132553).","DOI":"10.1109\/CVPR.2016.279"},{"key":"10.1016\/j.eswa.2023.121278_b23","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.isprsjprs.2020.03.010","article-title":"Global multi-scale grid integer coding and spatial indexing: A novel approach for big earth observation data","volume":"163","author":"Lei","year":"2020","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"key":"10.1016\/j.eswa.2023.121278_b24","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.inffus.2020.10.008","article-title":"Image retrieval from remote sensing big data: A survey","volume":"67","author":"Li","year":"2021","journal-title":"Information Fusion"},{"key":"10.1016\/j.eswa.2023.121278_b25","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.isprsjprs.2021.02.009","article-title":"Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation","volume":"175","author":"Li","year":"2021","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"issue":"11","key":"10.1016\/j.eswa.2023.121278_b26","doi-asserted-by":"crossref","first-page":"6521","DOI":"10.1109\/TGRS.2018.2839705","article-title":"Learning source-invariant deep hashing convolutional neural networks for cross-source remote sensing image retrieval","volume":"56","author":"Li","year":"2018","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"2","key":"10.1016\/j.eswa.2023.121278_b27","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/TGRS.2017.2756911","article-title":"Large-scale remote sensing image retrieval by deep hashing neural networks","volume":"56","author":"Li","year":"2017","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"2","key":"10.1016\/j.eswa.2023.121278_b28","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s11280-021-00865-8","article-title":"An integrated model based on deep multimodal and rank learning for point-of-interest recommendation","volume":"24","author":"Liao","year":"2021","journal-title":"World Wide Web"},{"key":"10.1016\/j.eswa.2023.121278_b29","doi-asserted-by":"crossref","unstructured":"Lin, Y., Liu, Z., Sun, M., Liu, Y., & Zhu, X. (2015). Learning entity and relation embeddings for knowledge graph completion. In Twenty-ninth AAAI conference on artificial intelligence.","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"10.1016\/j.eswa.2023.121278_b30","doi-asserted-by":"crossref","DOI":"10.1109\/TKDE.2022.3172903","article-title":"Graph self-supervised learning: A survey","author":"Liu","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2023.121278_b31","series-title":"European semantic web conference","first-page":"459","article-title":"MMKG: multi-modal knowledge graphs","author":"Liu","year":"2019"},{"key":"10.1016\/j.eswa.2023.121278_b32","series-title":"ICASSP 2022-2022 IEEE international conference on acoustics, speech and signal processing","first-page":"3278","article-title":"Contrastive knowledge graph attention network for request-based recipe recommendation","author":"Ma","year":"2022"},{"key":"10.1016\/j.eswa.2023.121278_b33","series-title":"Proc. Icml, vol. 30, no. 1","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","author":"Maas","year":"2013"},{"issue":"2","key":"10.1016\/j.eswa.2023.121278_b34","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1109\/TGRS.2016.2612821","article-title":"Convolutional neural networks for large-scale remote-sensing image classification","volume":"55","author":"Maggiori","year":"2016","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"8","key":"10.1016\/j.eswa.2023.121278_b35","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.3390\/math8081246","article-title":"Surface modeling from 2D contours with an application to craniofacial fracture construction","volume":"8","author":"Majeed","year":"2020","journal-title":"Mathematics"},{"key":"10.1016\/j.eswa.2023.121278_b36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2020\/4036434","article-title":"A novel generalization of trigonometric B\u00e9zier curve and surface with shape parameters and its applications","volume":"2020","author":"Maqsood","year":"2020","journal-title":"Mathematical Problems in Engineering"},{"key":"10.1016\/j.eswa.2023.121278_b37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13662-020-03001-4","article-title":"Geometric modeling and applications of generalized blended trigonometric B\u00e9zier curves with shape parameters","volume":"2020","author":"Maqsood","year":"2020","journal-title":"Advances in Difference Equations"},{"key":"10.1016\/j.eswa.2023.121278_b38","series-title":"2010 IEEE international conference on data mining","first-page":"995","article-title":"Factorization machines","author":"Rendle","year":"2010"},{"key":"10.1016\/j.eswa.2023.121278_b39","series-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"Rendle","year":"2012"},{"key":"10.1016\/j.eswa.2023.121278_b40","series-title":"International conference on medical image computing and computer-assisted intervention","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.eswa.2023.121278_b41","series-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"10.1016\/j.eswa.2023.121278_b42","doi-asserted-by":"crossref","unstructured":"Stojnic, V., & Risojevic, V. (2021). Self-supervised learning of remote sensing scene representations using contrastive multiview coding. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 1182\u20131191).","DOI":"10.1109\/CVPRW53098.2021.00129"},{"key":"10.1016\/j.eswa.2023.121278_b43","doi-asserted-by":"crossref","unstructured":"Sun, R., Cao, X., Zhao, Y., Wan, J., Zhou, K., Zhang, F., et al. (2020). Multi-modal knowledge graphs for recommender systems. In Proceedings of the 29th ACM international conference on information & knowledge management (pp. 1405\u20131414).","DOI":"10.1145\/3340531.3411947"},{"issue":"5","key":"10.1016\/j.eswa.2023.121278_b44","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2020.102277","article-title":"Mgat: Multimodal graph attention network for recommendation","volume":"57","author":"Tao","year":"2020","journal-title":"Information Processing & Management"},{"issue":"4","key":"10.1016\/j.eswa.2023.121278_b45","doi-asserted-by":"crossref","first-page":"JAMDSM0048","DOI":"10.1299\/jamdsm.2020jamdsm0048","article-title":"Some engineering applications of new trigonometric cubic b\u00e9zier-like curves to free-form complex curve modeling","volume":"14","author":"Usman","year":"2020","journal-title":"Journal of Advanced Mechanical Design, Systems, and Manufacturing"},{"key":"10.1016\/j.eswa.2023.121278_b46","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2023.121278_b47","series-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"10.1016\/j.eswa.2023.121278_b48","doi-asserted-by":"crossref","unstructured":"Wang, X., He, X., Cao, Y., Liu, M., & Chua, T. S. (2019). Kgat: Knowledge graph attention network for recommendation. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 950\u2013958).","DOI":"10.1145\/3292500.3330989"},{"key":"10.1016\/j.eswa.2023.121278_b49","doi-asserted-by":"crossref","unstructured":"Wang, X., He, X., Wang, M., Feng, F., & Chua, T. S. (2019). Neural graph collaborative filtering. In Proceedings of the 42nd International ACM SIGIR conference on research and development in information retrieval (pp. 165\u2013174).","DOI":"10.1145\/3331184.3331267"},{"key":"10.1016\/j.eswa.2023.121278_b50","doi-asserted-by":"crossref","unstructured":"Wang, J., Huang, P., Zhao, H., Zhang, Z., Zhao, B., & Lee, D. L. (2018). Billion-scale commodity embedding for e-commerce recommendation in alibaba. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 839\u2013848).","DOI":"10.1145\/3219819.3219869"},{"key":"10.1016\/j.eswa.2023.121278_b51","article-title":"KLGCN: Knowledge graph-aware light graph convolutional network for recommender systems","author":"Wang","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2023.121278_b52","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, F., Wang, J., Zhao, M., Li, W., Xie, X., et al. (2018). Ripplenet: Propagating user preferences on the knowledge graph for recommender systems. In Proceedings of the 27th ACM international conference on information and knowledge management (pp. 417\u2013426).","DOI":"10.1145\/3269206.3271739"},{"key":"10.1016\/j.eswa.2023.121278_b53","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, F., Xie, X., & Guo, M. (2018). DKN: Deep knowledge-aware network for news recommendation. In Proceedings of the 2018 world wide web conference (pp. 1835\u20131844).","DOI":"10.1145\/3178876.3186175"},{"key":"10.1016\/j.eswa.2023.121278_b54","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, F., Zhang, M., Leskovec, J., Zhao, M., Li, W., et al. (2019). Knowledge-aware graph neural networks with label smoothness regularization for recommender systems. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 968\u2013977).","DOI":"10.1145\/3292500.3330836"},{"key":"10.1016\/j.eswa.2023.121278_b55","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhao, M., Xie, X., Li, W., & Guo, M. (2019). Knowledge graph convolutional networks for recommender systems. In The world wide web conference (pp. 3307\u20133313).","DOI":"10.1145\/3308558.3313417"},{"key":"10.1016\/j.eswa.2023.121278_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119465","article-title":"To see further: Knowledge graph-aware deep graph convolutional network for recommender systems","author":"Wang","year":"2023","journal-title":"Information Sciences"},{"key":"10.1016\/j.eswa.2023.121278_b57","doi-asserted-by":"crossref","unstructured":"Wei, Y., Wang, X., Nie, L., He, X., Hong, R., & Chua, T. S. (2019). MMGCN: Multi-modal graph convolution network for personalized recommendation of micro-video. In Proceedings of the 27th ACM international conference on multimedia (pp. 1437\u20131445).","DOI":"10.1145\/3343031.3351034"},{"issue":"10","key":"10.1016\/j.eswa.2023.121278_b58","doi-asserted-by":"crossref","first-page":"1854","DOI":"10.1109\/TKDE.2019.2913394","article-title":"A hierarchical attention model for social contextual image recommendation","volume":"32","author":"Wu","year":"2019","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2023.121278_b59","series-title":"MM-rec: Multimodal news recommendation","author":"Wu","year":"2021"},{"issue":"6","key":"10.1016\/j.eswa.2023.121278_b60","doi-asserted-by":"crossref","first-page":"4197","DOI":"10.1109\/TII.2020.3008923","article-title":"Recommendation by users\u2019 multimodal preferences for smart city applications","volume":"17","author":"Xu","year":"2020","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"10.1016\/j.eswa.2023.121278_b61","doi-asserted-by":"crossref","unstructured":"Yang, Y., Huang, C., Xia, L., & Li, C. (2022). Knowledge graph contrastive learning for recommendation. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval (pp. 1434\u20131443).","DOI":"10.1145\/3477495.3532009"},{"key":"10.1016\/j.eswa.2023.121278_b62","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume":"33","author":"You","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"2","key":"10.1016\/j.eswa.2023.121278_b63","doi-asserted-by":"crossref","first-page":"40","DOI":"10.3390\/ijgi7020040","article-title":"A space-time periodic task model for recommendation of remote sensing images","volume":"7","author":"Zhang","year":"2018","journal-title":"ISPRS International Journal of Geo-Information"},{"key":"10.1016\/j.eswa.2023.121278_b64","doi-asserted-by":"crossref","unstructured":"Zhang, F., Yuan, N. J., Lian, D., Xie, X., & Ma, W. Y. (2016). Collaborative knowledge base embedding for recommender systems. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 353\u2013362).","DOI":"10.1145\/2939672.2939673"},{"issue":"2","key":"10.1016\/j.eswa.2023.121278_b65","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1109\/TMM.2017.2740022","article-title":"Social-aware movie recommendation via multimodal network learning","volume":"20","author":"Zhao","year":"2017","journal-title":"IEEE Transactions on Multimedia"},{"key":"10.1016\/j.eswa.2023.121278_b66","series-title":"Multi-modal knowledge graph construction and application: A survey","author":"Zhu","year":"2022"},{"key":"10.1016\/j.eswa.2023.121278_b67","doi-asserted-by":"crossref","unstructured":"Zou, D., Wei, W., Wang, Z., Mao, X. L., Zhu, F., Fang, R., et al. (2022). Improving knowledge-aware recommendation with multi-level interactive contrastive learning. In Proceedings of the 31st ACM international conference on information & knowledge management (pp. 2817\u20132826).","DOI":"10.1145\/3511808.3557358"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417423017803?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417423017803?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T23:33:18Z","timestamp":1733527998000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417423017803"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":67,"alternative-id":["S0957417423017803"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2023.121278","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2024,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MMKDGAT: Multi-modal Knowledge graph-aware Deep Graph Attention Network for remote sensing image recommendation","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2023.121278","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"121278"}}