{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:55:49Z","timestamp":1757314549703},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100013058","name":"Jiangsu Provincial Key Research and Development Program","doi-asserted-by":"publisher","award":["BE2018627"],"award-info":[{"award-number":["BE2018627"]}],"id":[{"id":"10.13039\/501100013058","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013094","name":"Science and Technology Planning Social Development Project of Zhenjiang City","doi-asserted-by":"publisher","award":["SH2021006"],"award-info":[{"award-number":["SH2021006"]}],"id":[{"id":"10.13039\/501100013094","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s10489-022-04200-0","type":"journal-article","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T01:02:50Z","timestamp":1666314170000},"page":"14058-14071","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Dual projection learning with adaptive graph smoothing for multi-label classification"],"prefix":"10.1007","volume":"53","author":[{"given":"Zhi-feng","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui-hang","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timothy Apasiba","family":"Abeo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong-hua","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang-Jun","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"key":"4200_CR1","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1016\/j.patcog.2018.01.022","volume":"78","author":"Y Liu","year":"2018","unstructured":"Liu Y, Wen K, Gao Q, Gao X, Nie F (2018) Svm based multi-label learning with missing labels for image annotation. Pattern Recognit. 78:307\u2013317","journal-title":"Pattern Recognit."},{"key":"4200_CR2","doi-asserted-by":"crossref","unstructured":"Gao S, Wu W, Lee C-H, Chua T-S (2004) A mfom learning approach to robust multiclass multi-label text categorization. In: Proceedings of the twenty-first international conference on Machine learning. Association for Computing Machinery, New York, p 42","DOI":"10.1145\/1015330.1015361"},{"issue":"7","key":"4200_CR3","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1093\/bioinformatics\/btk048","volume":"22","author":"Z Barut\u00e7uoglu","year":"2006","unstructured":"Barut\u00e7uoglu Z, Schapire RE, Troyanskaya OG (2006) Hierarchical multi-label prediction of gene function. Bioinformatics 22(7):830\u20136","journal-title":"Bioinformatics"},{"key":"4200_CR4","unstructured":"Sorower MS (2010) A literature survey on algorithms for multi-label learning, Oregon State University, Corvallis 18, 1\u201325."},{"key":"4200_CR5","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/TKDE.2013.39","volume":"26","author":"M-L Zhang","year":"2014","unstructured":"Zhang M-L, Zhou Z-H (2014) A review on multi-label learning algorithms. IEEE Trans Knowl Data Eng 26:1819\u20131837","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"4200_CR6","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/s11704-017-7031-7","volume":"12","author":"M-L Zhang","year":"2018","unstructured":"Zhang M-L, Li Y-K, Liu X-Y, Geng X (2018) Binary relevance for multi-label learning: an overview. Front Comput Sci 12(2):191\u2013202","journal-title":"Front Comput Sci"},{"key":"4200_CR7","doi-asserted-by":"crossref","unstructured":"Al-ma\u2019adeed S (2013) Kernel collaborative label power set system for multi-label classification. In: Qatar foundation annual research forum proceedings, ICTP 028","DOI":"10.5339\/qfarf.2013.ICTP-028"},{"key":"4200_CR8","doi-asserted-by":"crossref","unstructured":"Read J, Pfahringer B, Holmes G, Frank E (2009) Classifier chains for multi-label classification. In: Buntine W, Grobelnik M, Mladenic D, Shawe-Taylor J (eds) Machine learning and knowledge discovery in databases. ECML PKDD, Lecture Notes in Computer Science, vol 5782. Springer, Berlin, pp 254\u2013269","DOI":"10.1007\/978-3-642-04174-7_17"},{"key":"4200_CR9","unstructured":"Cl\u00e9men\u00e7on S, Vogel R (2020) A multiclass classification approach to label ranking. In: 23rd international conference on artificial intelligence and statistics. PMLR, Italy, pp 1421\u20131430"},{"key":"4200_CR10","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"M-L Zhang","year":"2007","unstructured":"Zhang M-L, Zhou Z-H (2007) Ml-knn: a lazy learning approach to multi-label learning. Pattern Recog 40:2038\u20132048","journal-title":"Pattern Recog"},{"key":"4200_CR11","doi-asserted-by":"crossref","unstructured":"Clare A, King R (2001) Knowledge discovery in multi-label phenotype data. In: De Raedt L, Siebes A (eds) Principles of data mining and knowledge discovery. PKDD 2001. Lecture notes in computer science, vol 2168. Springer, Berlin","DOI":"10.1007\/3-540-44794-6_4"},{"key":"4200_CR12","doi-asserted-by":"publisher","first-page":"3309","DOI":"10.1109\/TKDE.2016.2608339","volume":"28","author":"J Huang","year":"2016","unstructured":"Huang J, Li G, Huang Q, Wu X (2016) Learning label-specific features and class-dependent labels for multi-label classification. IEEE Trans Knowl Data Eng 28:3309\u20133323","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"4200_CR13","unstructured":"Jian L, Li J, Shu K, Liu H (2016) Multi-label informed feature selection. In: Proceedings of the twenty-fifth international joint conference on artificial intelligence (IJCAI-16), pp 1627\u20131633."},{"key":"4200_CR14","doi-asserted-by":"crossref","unstructured":"Kashef S, Nezamabadi-Pour H (2017) An effective method of multi-label feature selection employing evolutionary algorithms. In: 2017 2nd conference on swarm intelligence and evolutionary computation (CSIEC), pp 21\u201325","DOI":"10.1109\/CSIEC.2017.7940162"},{"key":"4200_CR15","doi-asserted-by":"publisher","first-page":"107423","DOI":"10.1016\/j.patcog.2020.107423","volume":"106","author":"B Jia","year":"2019","unstructured":"Jia B, Zhang M-L (2019) Multi-dimensional classification via knn feature augmentation. Pattern Recog 106:107423","journal-title":"Pattern Recog"},{"key":"4200_CR16","doi-asserted-by":"crossref","unstructured":"Kimura K, Kudo M, Sun L (2016) Simultaneous nonlinear label-instance embedding for multi-label classification. In: S+SSPR","DOI":"10.1007\/978-3-319-49055-7_2"},{"key":"4200_CR17","unstructured":"Huang S-J, Zhou Z-H (2012) Multi-label learning by exploiting label correlations locally. In: AAAI"},{"key":"4200_CR18","unstructured":"Bhatia K, Jain H, Kar P, Varma M, Jain P (2015) Sparse local embeddings for extreme multi-label classification. In: NIPS"},{"key":"4200_CR19","first-page":"1529","volume":"2","author":"Y-N Chen","year":"2012","unstructured":"Chen Y-N, Lin H-T (2012) Feature-aware label space dimension reduction for multi-label classification. Adv Neural Inf Process Syst 2:1529\u20131537","journal-title":"Adv Neural Inf Process Syst"},{"key":"4200_CR20","unstructured":"Lin Z, Ding G, Hu M, Wang J (2014) Multi-label classification via feature-aware implicit label space encoding. In: ICML"},{"key":"4200_CR21","doi-asserted-by":"crossref","unstructured":"Jolliffe IT (1986) Principal component analysis and factor analysis. In: Principal component analysis. Springer series in statistics. Springer, New York","DOI":"10.1007\/978-1-4757-1904-8"},{"key":"4200_CR22","doi-asserted-by":"publisher","first-page":"20289","DOI":"10.1109\/ACCESS.2020.2969238","volume":"8","author":"J Huang","year":"2020","unstructured":"Huang J, Zhang P, Zhang H, Li G, Rui H (2020) Multi-label learning via feature and label space dimension reduction. IEEE Access 8:20289\u201320303","journal-title":"IEEE Access"},{"key":"4200_CR23","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.patcog.2019.01.009","volume":"90","author":"V Kumar","year":"2019","unstructured":"Kumar V, Pujari AK, Padmanabhan V, Kagita V (2019) Group preserving label embedding for multi-label classification. Pattern Recog 90:23\u201334","journal-title":"Pattern Recog"},{"key":"4200_CR24","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.1109\/TKDE.2017.2785795","volume":"30","author":"Y Zhu","year":"2018","unstructured":"Zhu Y, Kwok JT-Y, Zhou Z-H (2018) Multi-label learning with global and local label correlation. IEEE Trans Knowl Data Eng 30:1081\u20131094","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"4200_CR25","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.patrec.2018.08.021","volume":"112","author":"R Huang","year":"2018","unstructured":"Huang R, Jiang W, Sun G (2018) Manifold-based constraint laplacian score for multi-label feature selection. Pattern Recog Lett 112:346\u2013352","journal-title":"Pattern Recog Lett"},{"key":"4200_CR26","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1007\/s13042-017-0647-y","volume":"9","author":"Z Cai","year":"2018","unstructured":"Cai Z, Zhu W (2018) Multi-label feature selection via feature manifold learning and sparsity regularization. Int J Mach Learn Cybern 9:1321\u20131334","journal-title":"Int J Mach Learn Cybern"},{"key":"4200_CR27","unstructured":"He X, Niyogi P (2003) Locality preserving projections. In: NIPS"},{"key":"4200_CR28","unstructured":"Lin Z, Chen M, Ma Y The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Mathematical Programming 9"},{"key":"4200_CR29","first-page":"2411","volume":"12","author":"G Tsoumakas","year":"2011","unstructured":"Tsoumakas G, Xioufis ES, Vilcek J, Vlahavas IP (2011) Mulan: a java library for multi-label learning. J Mach Learn Res 12:2411\u20132414","journal-title":"J Mach Learn Res"},{"key":"4200_CR30","unstructured":"Bi W, Kwok JT-Y (2013) Efficient multi-label classification with many labels. In: ICML"},{"key":"4200_CR31","doi-asserted-by":"publisher","first-page":"2508","DOI":"10.1162\/NECO_a_00320","volume":"24","author":"F Tai","year":"2012","unstructured":"Tai F, Lin H-T (2012) Multilabel classification with principal label space transformation. Neural Comput 24:2508\u20132542","journal-title":"Neural Comput"},{"key":"4200_CR32","unstructured":"Jia B, Zhang M-L (2021) Maximum margin multi-dimensional classification. In: IEEE transactions on neural networks and learning systems. IEEE, New Jersey, pp 1\u201314"},{"key":"4200_CR33","doi-asserted-by":"publisher","first-page":"222102","DOI":"10.1007\/s11432-019-2905-3","volume":"63","author":"B Jia","year":"2020","unstructured":"Jia B, Zhang M-L (2020) Multi-dimensional classification via stacked dependency exploitation. Sci China Inf Sci 63:222102","journal-title":"Sci China Inf Sci"},{"key":"4200_CR34","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1198\/jasa.2004.s339","volume":"99","author":"D Ruppert","year":"2004","unstructured":"Ruppert D (2004) The elements of statistical learning: data mining, inference, and prediction. J Am Stat Assoc 99:567\u2013567","journal-title":"J Am Stat Assoc"},{"key":"4200_CR35","doi-asserted-by":"publisher","first-page":"27:1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"C-C Chang","year":"2011","unstructured":"Chang C-C, Lin C-J (2011) Libsvm: a library for support vector machines. ACM Trans Intell Syst Technol 2:27:1\u201327:27","journal-title":"ACM Trans Intell Syst Technol"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04200-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-04200-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04200-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T10:33:49Z","timestamp":1685529229000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-04200-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":35,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["4200"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-04200-0","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"21 September 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}