{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:37:16Z","timestamp":1760575036846,"version":"build-2065373602"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T00:00:00Z","timestamp":1750550400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T00:00:00Z","timestamp":1750550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62166032","62166032","62162053","62462052","62166032"],"award-info":[{"award-number":["62166032","62166032","62162053","62462052","62166032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012579","name":"Natural Science Foundation of Qinghai Province","doi-asserted-by":"publisher","award":["2023-ZJ-906M","2023-ZJ-906M","2023-ZJ-906M"],"award-info":[{"award-number":["2023-ZJ-906M","2023-ZJ-906M","2023-ZJ-906M"]}],"id":[{"id":"10.13039\/501100012579","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s10115-025-02512-4","type":"journal-article","created":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T11:15:31Z","timestamp":1750590931000},"page":"9501-9529","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Vector knowledge transfer-driven representation learning for heterogeneous hypernetworks"],"prefix":"10.1007","volume":"67","author":[{"given":"Yijian","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoying","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqiang","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tengfei","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,22]]},"reference":[{"issue":"6","key":"2512_CR1","doi-asserted-by":"publisher","first-page":"7646","DOI":"10.1109\/TCSS.2024.3434737","volume":"11","author":"K Wang","year":"2024","unstructured":"Wang K, Zhu Y, Wang X, Huang J, Cao T (2024) Heterogeneous hypernetwork representation learning with hyperedge fusion. IEEE Trans Comput Soc Syst 11(6):7646\u20137657","journal-title":"IEEE Trans Comput Soc Syst"},{"key":"2512_CR2","doi-asserted-by":"publisher","first-page":"3293","DOI":"10.1007\/s10115-024-02311-3","volume":"67","author":"A Paul","year":"2025","unstructured":"Paul A, Wu Z, Chen B, Luo K, Fang L (2025) Interpretable adversarial neural pairwise ranking for academic network embedding. Knowl Inf Syst 67:3293\u20133315","journal-title":"Knowl Inf Syst"},{"doi-asserted-by":"crossref","unstructured":"Perozzi B, Ai-Rfou R, Skiena S (2014) DeepWalk: online learning of social representations. In: Proceedings of 20th ACM SIGKDD international conference on knowledge discovery and data mining, pp 697\u2013706","key":"2512_CR3","DOI":"10.1145\/2623330.2623732"},{"doi-asserted-by":"crossref","unstructured":"Grover A, Leskovec J (2016) Node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pp 855\u2013864","key":"2512_CR4","DOI":"10.1145\/2939672.2939754"},{"issue":"2","key":"2512_CR5","doi-asserted-by":"publisher","first-page":"276","DOI":"10.3390\/e24020276","volume":"24","author":"L Zhan","year":"2022","unstructured":"Zhan L, Jia T (2022) CoarSAS2hvec: heterogeneous information network embedding with balanced network sampling. Entropy 24(2):276","journal-title":"Entropy"},{"unstructured":"Xie J, Yang Y, Wang Z, Wu L (2024) Learning fair representations for recommendation via information bottleneck principle. In: Proceedings of the 33rd international joint conference on artificial intelligence, pp 2469\u20132477","key":"2512_CR6"},{"key":"2512_CR7","doi-asserted-by":"publisher","first-page":"7837","DOI":"10.1007\/s10115-024-02188-2","volume":"66","author":"Z Yu","year":"2024","unstructured":"Yu Z, Wang J, Luo W, Tse R, Pau G (2024) Multi-perspective patient representation learning for disease prediction on electronic health records. Knowl Inf Syst 66:7837\u20137858","journal-title":"Knowl Inf Syst"},{"key":"2512_CR8","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1007\/s10115-023-01963-x","volume":"66","author":"S Li","year":"2024","unstructured":"Li S, Zaidi N, Du M, Zhou Z, Zhang H, Li G (2024) Property graph representation learning for node classification. Knowl Inf Syst 66:237\u2013265","journal-title":"Knowl Inf Syst"},{"doi-asserted-by":"crossref","unstructured":"Agarwal S, Branson K, Belongie S (2006) Higher order learning with graphs. In: Proceedings of the 23rd international conference on Machine learning, pp 17\u201324","key":"2512_CR9","DOI":"10.1145\/1143844.1143847"},{"doi-asserted-by":"crossref","unstructured":"Yu L, Shen X, Jiang X, Yang J, Zhong D (2019) Hypergraph clustering based on intra-class scatter matrix for mining higher-order microbial module. In: Proceedings of 2019 IEEE international conference on bioinformatics and biomedicine, pp 240\u2013243","key":"2512_CR10","DOI":"10.1109\/BIBM47256.2019.8983390"},{"issue":"1\u20133","key":"2512_CR11","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/0012-365X(93)90322-K","volume":"117","author":"M Bolla","year":"1993","unstructured":"Bolla M (1993) Spectra, Euclidean representations and clusterings of hypergraphs. Discret Math 117(1\u20133):19\u201339","journal-title":"Discret Math"},{"doi-asserted-by":"crossref","unstructured":"Zhou D, Huang J, Scholkopf B (2007) Learning with hypergraphs: clustering classification and embedding. In: Proceedings of the 19th conference on neural information processing systems, pp 1601\u20131608","key":"2512_CR12","DOI":"10.7551\/mitpress\/7503.003.0205"},{"doi-asserted-by":"crossref","unstructured":"Huang J, Chen C, Ye F, Wu J, Zheng Z, Ling G (2019) Hyper2vec: biased random walk for hyper-network embedding. In: Proceedings of international conference on database systems for advanced applications, pp 273\u2013277","key":"2512_CR13","DOI":"10.1007\/978-3-030-18590-9_27"},{"doi-asserted-by":"crossref","unstructured":"Feng Y, You H, Zhang Z, Ji R, Gao Y (2019) Hypergraph neural networks. In: Proceedings of 33rd AAAI conference on artificial intelligence, pp 3558\u20133565","key":"2512_CR14","DOI":"10.1609\/aaai.v33i01.33013558"},{"doi-asserted-by":"crossref","unstructured":"Ji S, Feng Y, Ji R, Zhao X, Tang W, Gao Y (2020) Dual channel hypergraph collaborative filtering. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, pp 2020\u20132029","key":"2512_CR15","DOI":"10.1145\/3394486.3403253"},{"doi-asserted-by":"crossref","unstructured":"Huang J, Liu X, Song Y (2019) Hyper-path-based representation learning for hyper-networks. In: Proceedings of the 28th ACM international conference on information and knowledge management, pp 449\u2013458","key":"2512_CR16","DOI":"10.1145\/3357384.3357871"},{"unstructured":"Mikolov T, Sutskever L, Chen K, Corrado G, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Proceedings of the 27th international conference on neural information processing systems, pp 3111\u20133119","key":"2512_CR17"},{"doi-asserted-by":"crossref","unstructured":"Tu K, Cui P, Wang X, Wang F, Zhu W (2018) Structural deep embedding for hyper-networks. In: Proceedings of the 32nd AAAI conference on artificial intelligence, pp 426\u2013433","key":"2512_CR18","DOI":"10.1609\/aaai.v32i1.11266"},{"unstructured":"Zhang R, Zou Y, Ma J (2020) Hyper-SAGNN: a self-attention based graph neural network for hypergraphs. In: Proceedings of the 8th international conference on learning representations, pp 1\u201318","key":"2512_CR19"},{"unstructured":"Liu S, Lai C, Toriumi F (2023) HyperS2V: a framework for structural representation of nodes in hyper networks. arXiv:2311.04149","key":"2512_CR20"},{"issue":"1","key":"2512_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s44336-024-00008-3","volume":"1","author":"J Xue","year":"2024","unstructured":"Xue J, Xing L, Wang Y, Fan X, Kong L, Zhang Q, Nie F, Li X (2024) A comprehensive survey of fast graph clustering. Vicinagearth 1(1):1\u201322","journal-title":"Vicinagearth"},{"issue":"9","key":"2512_CR22","doi-asserted-by":"publisher","first-page":"9743","DOI":"10.1109\/TKDE.2023.3249475","volume":"35","author":"J Xie","year":"2023","unstructured":"Xie J, Kong W, Xia S, Wang G, Gao X (2023) An efficient spectral clustering algorithm based on granular-ball. IEEE Trans Knowl Data Eng 35(9):9743\u20139753","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2512_CR23","doi-asserted-by":"publisher","first-page":"102799","DOI":"10.1016\/j.aei.2024.102799","volume":"62","author":"J Singh","year":"2024","unstructured":"Singh J, Singh D (2024) A comprehensive review of clustering techniques in artificial intelligence for knowledge discovery: taxonomy, challenges, applications and future prospects. Adv Eng Inform 62:102799","journal-title":"Adv Eng Inform"},{"unstructured":"Berahmand K, Saberi-Movahed F, Sheikhpour R, Li Y, Jalili M (2025) A comprehensive survey on spectral clustering with graph structure learning. arXiv:2501.13597","key":"2512_CR24"},{"key":"2512_CR25","doi-asserted-by":"publisher","first-page":"1718","DOI":"10.1109\/ACCESS.2017.2780109","volume":"6","author":"J Wang","year":"2017","unstructured":"Wang J, Zhu C, Zhou Y, Zhu X, Wang Y, Zhang W (2017) From partition-based clustering to density-based clustering: fast find clusters with diverse shapes and densities in spatial databases. IEEE Access 6:1718\u20131729","journal-title":"IEEE Access"},{"key":"2512_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v091.i01","volume":"91","author":"M Hahsler","year":"2019","unstructured":"Hahsler M, Piekenbrock M, Doran D (2019) DBSCAN: fast density based clustering with R. J Stat Softw 91:1\u201330","journal-title":"J Stat Softw"},{"issue":"1","key":"2512_CR27","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/TNSE.2022.3210233","volume":"10","author":"K Berahmand","year":"2022","unstructured":"Berahmand K, Mohammadi M, Saberi-Movahed F, Li Y, Xu Y (2022) Graph regularized nonnegative matrix factorization for community detection in attributed networks. IEEE Trans Netw Sci Eng 10(1):372\u2013385","journal-title":"IEEE Trans Netw Sci Eng"},{"issue":"4","key":"2512_CR28","doi-asserted-by":"publisher","first-page":"5858","DOI":"10.1109\/TNNLS.2024.3403155","volume":"36","author":"Y Ren","year":"2024","unstructured":"Ren Y, Pu J, Yang Z, Xu J, Li G, Pu X, Philip S, He L (2024) Deep clustering: a comprehensive survey. IEEE Trans Neural Netw Learn Syst 36(4):5858\u20135878","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"doi-asserted-by":"crossref","unstructured":"Louis A (2015) Hypergraph Markov operators, eigenvalues and approximation algorithms. In: Proceedings of the 47th annual ACM symposium on theory of computing, pp 713\u2013722","key":"2512_CR29","DOI":"10.1145\/2746539.2746555"},{"key":"2512_CR30","doi-asserted-by":"publisher","first-page":"110882","DOI":"10.1016\/j.patcog.2024.110882","volume":"157","author":"R Sheikhpour","year":"2025","unstructured":"Sheikhpour R, Berahmand K, Mohammadi M, Khosravi H (2025) Sparse feature selection using hypergraph Laplacian-based semi-supervised discriminant analysis. Pattern Recogn 157:110882","journal-title":"Pattern Recogn"},{"key":"2512_CR31","doi-asserted-by":"publisher","first-page":"022308","DOI":"10.1103\/PhysRevE.101.022308","volume":"101","author":"T Carletti","year":"2020","unstructured":"Carletti T, Battiston F, Cencetti G, Fancelli D (2020) Random walks on hypergraphs. Phys Rev E 101:022308","journal-title":"Phys Rev E"},{"doi-asserted-by":"crossref","unstructured":"Yi J, Park J (2020) Hypergraph convolutional recurrent neural network. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, pp 3366\u20133376","key":"2512_CR32","DOI":"10.1145\/3394486.3403389"},{"issue":"4","key":"2512_CR33","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1109\/TNNLS.2019.2919676","volume":"31","author":"Y Chu","year":"2020","unstructured":"Chu Y, Fei J, Hou S (2020) Adaptive global sliding-mode control for dynamic systems using double hidden layer recurrent neural network structure. IEEE Trans Neural Netw Learn Syst 31(4):1297\u20131309","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2512_CR34","doi-asserted-by":"publisher","first-page":"125534","DOI":"10.1016\/j.eswa.2024.125534","volume":"261","author":"S Nejadshamsi","year":"2025","unstructured":"Nejadshamsi S, Bentahar J, Eicker U, Wang C, Jamshidi F (2025) A geographic-semantic context-aware urban commuting flow prediction model using graph neural network. Expert Syst Appl 261:125534","journal-title":"Expert Syst Appl"},{"doi-asserted-by":"crossref","unstructured":"Wu L, Yang Y, Chen L, Lian D, Hong R, Wang M (2020) Learning to transfer graph embeddings for inductive graph based recommendation. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval, pp 1211\u20131220","key":"2512_CR35","DOI":"10.1145\/3397271.3401145"},{"issue":"12","key":"2512_CR36","doi-asserted-by":"publisher","first-page":"10297","DOI":"10.1109\/TPAMI.2024.3445463","volume":"46","author":"C Chen","year":"2024","unstructured":"Chen C, Wu Y, Dai Q, Zhou H, Xu M, Yang S (2024) A survey on graph neural networks and graph transformers in computer vision: a task-oriented perspective. IEEE Trans Pattern Anal Mach Intell 46(12):10297\u201310318","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2512_CR37","doi-asserted-by":"publisher","first-page":"6561","DOI":"10.1007\/s10115-024-02192-6","volume":"66","author":"A Gautam","year":"2024","unstructured":"Gautam A, Raza Z (2024) Disease outbreak prediction using natural language processing: a review. Knowl Inf Syst 66:6561\u20136595","journal-title":"Knowl Inf Syst"},{"issue":"5","key":"2512_CR38","doi-asserted-by":"publisher","first-page":"3279","DOI":"10.1109\/TETCI.2024.3375019","volume":"8","author":"Y Wang","year":"2024","unstructured":"Wang Y, Ishibuchi H, Pedrycz W, Zhu J, Cao X, Wang J (2024) Convolutional fuzzy neural networks with random weights for image classification. IEEE Trans Emerg Top Comput Intell 8(5):3279\u20133293","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"issue":"8","key":"2512_CR39","doi-asserted-by":"publisher","first-page":"5031","DOI":"10.1109\/TII.2022.3146552","volume":"18","author":"I Ahmed","year":"2022","unstructured":"Ahmed I, Jeon G, Piccialli F (2022) From artificial intelligence to explainable artificial intelligence in industry 4.0: a survey on what, how, and where. IEEE Trans Ind Inform 18(8):5031\u20135042","journal-title":"IEEE Trans Ind Inform"},{"doi-asserted-by":"crossref","unstructured":"Zheng V, Cao B, Zheng Y, Xie X, Yang Q (2010) Collaborative filtering meets mobile recommendation: a user-centered approach. In: Proceedings of the 24th AAAI conference on artificial intelligence, pp 236\u2013241","key":"2512_CR40","DOI":"10.1609\/aaai.v24i1.7577"},{"issue":"4","key":"2512_CR41","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2827872","volume":"5","author":"F Harper","year":"2015","unstructured":"Harper F, Konstan J (2015) The movielens datasets: history and context. ACM Trans Interact Intell Syst 5(4):1\u201319","journal-title":"ACM Trans Interact Intell Syst"},{"issue":"11","key":"2512_CR42","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"G Miller","year":"1995","unstructured":"Miller G (1995) WordNet: a lexical database for English. Commun ACM 38(11):39\u201341","journal-title":"Commun ACM"},{"unstructured":"Behrouz A, Hashemi F, Sadeghian S, Seltzer M (2023) CAT-Walk: inductive hypergraph learning via set walks. In: Proceedings of 37th conference on neural information processing systems, pp 1\u201336","key":"2512_CR43"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02512-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-025-02512-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02512-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T10:58:52Z","timestamp":1760525932000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-025-02512-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,22]]},"references-count":43,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["2512"],"URL":"https:\/\/doi.org\/10.1007\/s10115-025-02512-4","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"type":"print","value":"0219-1377"},{"type":"electronic","value":"0219-3116"}],"subject":[],"published":{"date-parts":[[2025,6,22]]},"assertion":[{"value":"16 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}