{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:25:52Z","timestamp":1743103552114,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031781650"},{"type":"electronic","value":"9783031781667"}],"license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78166-7_27","type":"book-chapter","created":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T21:35:22Z","timestamp":1733088922000},"page":"414-429","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Label-Specific Multi-label Classification with\u00a0Entropy Guided Clustering"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8232-5228","authenticated-orcid":false,"given":"Jiaxuan","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7408-6319","authenticated-orcid":false,"given":"Tong","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7173-7793","authenticated-orcid":false,"given":"Xiaoyan","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3862-6557","authenticated-orcid":false,"given":"Jiayin","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"27_CR1","doi-asserted-by":"crossref","unstructured":"Boutell, M.R., Luo, J., Shen, X., Brown, C.M.: Learning multi-label scene classification. Pattern recogn. 37(9), 1757\u20131771 (2004)","DOI":"10.1016\/j.patcog.2004.03.009"},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Z.M., Wei, X.S., Wang, P., Guo, Y.: Multi-label image recognition with graph convolutional networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5177\u20135186 (2019)","DOI":"10.1109\/CVPR.2019.00532"},{"key":"27_CR3","doi-asserted-by":"crossref","unstructured":"Clare, A., King, R.D.: Knowledge discovery in multi-label phenotype data. In: European Conference on Principles of Data Mining and Knowledge Discovery, pp. 42\u201353. Springer (2001)","DOI":"10.1007\/3-540-44794-6_4"},{"key":"27_CR4","doi-asserted-by":"publisher","first-page":"109945","DOI":"10.1016\/j.patcog.2023.109945","volume":"145","author":"J Dai","year":"2024","unstructured":"Dai, J., Huang, W., Zhang, C., Liu, J.: Multi-label feature selection by strongly relevant label gain and label mutual aid. Pattern Recogn. 145, 109945 (2024)","journal-title":"Pattern Recogn."},{"key":"27_CR5","first-page":"681","volume":"14","author":"A Elisseeff","year":"2001","unstructured":"Elisseeff, A., Weston, J.: A kernel method for multi-labelled classification. Adv. Neural. Inf. Process. Syst. 14, 681\u2013687 (2001)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"6","key":"27_CR6","doi-asserted-by":"publisher","first-page":"3375","DOI":"10.1007\/s10489-020-02008-4","volume":"51","author":"Y Guan","year":"2021","unstructured":"Guan, Y., Li, W., Zhang, B., Han, B., Ji, M.: Multi-label classification by formulating label-specific features from simultaneous instance level and feature level. Appl. Intell. 51(6), 3375\u20133390 (2021)","journal-title":"Appl. Intell."},{"issue":"2","key":"27_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3319911","volume":"13","author":"Y Guo","year":"2019","unstructured":"Guo, Y., Chung, F., Li, G., Wang, J., Gee, J.C.: Leveraging label-specific discriminant mapping features for multi-label learning. ACM Trans. Knowl. Discov. Data (TKDD) 13(2), 1\u201323 (2019)","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"key":"27_CR8","doi-asserted-by":"publisher","first-page":"11474","DOI":"10.1109\/ACCESS.2019.2891611","volume":"7","author":"H Han","year":"2019","unstructured":"Han, H., Huang, M., Zhang, Y., Yang, X., Feng, W.: Multi-label learning with label specific features using correlation information. IEEE Access 7, 11474\u201311484 (2019)","journal-title":"IEEE Access"},{"issue":"12","key":"27_CR9","doi-asserted-by":"publisher","first-page":"9860","DOI":"10.1109\/TPAMI.2021.3136592","volume":"44","author":"JY Hang","year":"2021","unstructured":"Hang, J.Y., Zhang, M.L.: Collaborative learning of label semantics and deep label-specific features for multi-label classification. IEEE Trans. Pattern Anal. Mach. Intell. 44(12), 9860\u20139871 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR10","doi-asserted-by":"crossref","unstructured":"Huang, J., Li, G., Huang, Q., Wu, X.: Learning label specific features for multi-label classification. In: 2015 IEEE International Conference on Data Mining, pp. 181\u2013190. IEEE (2015)","DOI":"10.1109\/ICDM.2015.67"},{"issue":"12","key":"27_CR11","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.: Learning label-specific features and class-dependent labels for multi-label classification. IEEE Trans. Knowl. Data Eng. 28(12), 3309\u20133323 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"27_CR12","doi-asserted-by":"publisher","first-page":"110505","DOI":"10.1016\/j.patcog.2024.110505","volume":"153","author":"J Li","year":"2024","unstructured":"Li, J., Zhu, X., Zhang, W., Wang, J.: A ranking-based problem transformation method for weakly supervised multi-label learning. Pattern Recogn. 153, 110505 (2024)","journal-title":"Pattern Recogn."},{"key":"27_CR13","doi-asserted-by":"publisher","first-page":"108259","DOI":"10.1016\/j.patcog.2021.108259","volume":"121","author":"J Li","year":"2022","unstructured":"Li, J., Li, P., Hu, X., Yu, K.: Learning common and label-specific features for multi-label classification with correlation information. Pattern Recogn. 121, 108259 (2022)","journal-title":"Pattern Recogn."},{"issue":"3","key":"27_CR14","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1109\/TCYB.2016.2526058","volume":"47","author":"S Pan","year":"2016","unstructured":"Pan, S., Wu, J., Zhu, X., Long, G., Zhang, C.: Task sensitive feature exploration and learning for multitask graph classification. IEEE Trans. Cybern. 47(3), 744\u2013758 (2016)","journal-title":"IEEE Trans. Cybern."},{"key":"27_CR15","doi-asserted-by":"crossref","unstructured":"Read, J., Pfahringer, B., Holmes, G., Frank, E.: Classifier chains for multi-label classification. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 254\u2013269. Springer (2009)","DOI":"10.1007\/978-3-642-04174-7_17"},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Sechidis, K., Tsoumakas, G., Vlahavas, I.: On the stratification of multi-label data. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 145\u2013158. Springer (2011)","DOI":"10.1007\/978-3-642-23808-6_10"},{"issue":"8","key":"27_CR17","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888\u2013905 (2000)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR18","unstructured":"Strehl, A., Ghosh, J.: Cluster ensembles\u2014a knowledge reuse framework for combining multiple partitions. J. Mach. Learn. Res. 3(Dec), 583\u2013617 (2002)"},{"key":"27_CR19","doi-asserted-by":"crossref","unstructured":"Tsoumakas, G., Vlahavas, I.: Random k-labelsets: An ensemble method for multilabel classification. In: European Conference on Machine Learning, pp. 406\u2013417. Springer (2007)","DOI":"10.1007\/978-3-540-74958-5_38"},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: On the value of head labels in multi-label text classification. ACM Trans. Knowl. Discov. Data 18(5), 1\u201321 (2024)","DOI":"10.1145\/3643853"},{"issue":"7","key":"27_CR21","doi-asserted-by":"publisher","first-page":"1248","DOI":"10.1109\/JAS.2022.105518","volume":"9","author":"YB Wang","year":"2022","unstructured":"Wang, Y.B., Hang, J.Y., Zhang, M.L.: Stable label-specific features generation for multi-label learning via mixture-based clustering ensemble. IEEE\/CAA J. Automatica Sinica 9(7), 1248\u20131261 (2022)","journal-title":"IEEE\/CAA J. Automatica Sinica"},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Wei, X., Yu, Z., Zhang, C., Hu, Q.: Ensemble of label specific features for multi-label classification. In: 2018 IEEE International Conference on Multimedia and Expo (ICME), pp.\u00a01\u20136. IEEE (2018)","DOI":"10.1109\/ICME.2018.8486444"},{"issue":"16","key":"27_CR23","doi-asserted-by":"publisher","first-page":"2032","DOI":"10.1093\/bioinformatics\/btt320","volume":"29","author":"YY Xu","year":"2013","unstructured":"Xu, Y.Y., Yang, F., Zhang, Y., Shen, H.B.: An image-based multi-label human protein subcellular localization predictor (i locator) reveals protein mislocalizations in cancer tissues. Bioinformatics 29(16), 2032\u20132040 (2013)","journal-title":"Bioinformatics"},{"key":"27_CR24","doi-asserted-by":"crossref","unstructured":"Ye, H., Sunderraman, R., Ji, S.: MatchXML: an efficient text-label matching framework for extreme multi-label text classification. IEEE Trans. Knowl. Data Eng. (2024)","DOI":"10.1109\/TKDE.2024.3374750"},{"key":"27_CR25","doi-asserted-by":"crossref","unstructured":"Zhan, W., Zhang, M.L.: Multi-label learning with label-specific features via clustering ensemble. In: 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 129\u2013136. IEEE (2017)","DOI":"10.1109\/DSAA.2017.75"},{"key":"27_CR26","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.neucom.2020.07.107","volume":"419","author":"C Zhang","year":"2021","unstructured":"Zhang, C., Li, Z.: Multi-label learning with label-specific features via weighting and label entropy guided clustering ensemble. Neurocomputing 419, 59\u201369 (2021)","journal-title":"Neurocomputing"},{"key":"27_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, J.J., Fang, M., Li, X.: Multi-label learning based on label entropy guided clustering. In: 2014 IEEE International Conference on Computer and Information Technology, pp. 756\u2013760. IEEE (2014)","DOI":"10.1109\/CIT.2014.65"},{"key":"27_CR28","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/j.neucom.2014.11.062","volume":"154","author":"JJ Zhang","year":"2015","unstructured":"Zhang, J.J., Fang, M., Li, X.: Multi-label learning with discriminative features for each label. Neurocomputing 154, 305\u2013316 (2015)","journal-title":"Neurocomputing"},{"issue":"1","key":"27_CR29","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/TPAMI.2014.2339815","volume":"37","author":"ML Zhang","year":"2014","unstructured":"Zhang, M.L., Wu, L.: Lift: multi-label learning with label-specific features. IEEE Trans. Pattern Anal. Mach. Intell. 37(1), 107\u2013120 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"27_CR30","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"ML Zhang","year":"2007","unstructured":"Zhang, M.L., Zhou, Z.H.: ML-KNN: a lazy learning approach to multi-label learning. Pattern Recogn. 40(7), 2038\u20132048 (2007)","journal-title":"Pattern Recogn."},{"key":"27_CR31","doi-asserted-by":"publisher","first-page":"110411","DOI":"10.1016\/j.patcog.2024.110411","volume":"151","author":"Y Zhang","year":"2024","unstructured":"Zhang, Y., Huo, W., Tang, J.: Multi-label feature selection via latent representation learning and dynamic graph constraints. Pattern Recogn. 151, 110411 (2024)","journal-title":"Pattern Recogn."},{"key":"27_CR32","doi-asserted-by":"crossref","unstructured":"Zhu, K., Fu, M., Wu, J.: Multi-label self-supervised learning with scene images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6694\u20136703 (2023)","DOI":"10.1109\/ICCV51070.2023.00616"},{"key":"27_CR33","doi-asserted-by":"crossref","unstructured":"Zhu, X., Lu, W.: Multi-label classification with dual tail-node augmentation for drug repositioning. IEEE\/ACM Trans. Comput. Biol. Bioinform. (2023)","DOI":"10.1109\/TCBB.2023.3292883"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78166-7_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T23:38:51Z","timestamp":1733096331000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78166-7_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,2]]},"ISBN":["9783031781650","9783031781667"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78166-7_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,2]]},"assertion":[{"value":"2 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}