{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:57:32Z","timestamp":1742950652725,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811684296"},{"type":"electronic","value":"9789811684302"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-8430-2_17","type":"book-chapter","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T18:02:42Z","timestamp":1641319362000},"page":"179-188","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["BioBERT Based Efficient Clustering Framework for Biomedical Document Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9375-7621","authenticated-orcid":false,"given":"Khishigsuren","family":"Davagdorj","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7133-3051","authenticated-orcid":false,"given":"Kwang Ho","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8399-655X","authenticated-orcid":false,"given":"Tsatsral","family":"Amarbayasgalan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6740-219X","authenticated-orcid":false,"given":"Lkhagvadorj","family":"Munkhdalai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8956-0511","authenticated-orcid":false,"given":"Ling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3931-7905","authenticated-orcid":false,"given":"Meijing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0394-9054","authenticated-orcid":false,"given":"Keun Ho","family":"Ryu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,4]]},"reference":[{"key":"17_CR1","series-title":"Smart Innovation, Systems and Technologies","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1007\/978-981-33-6757-9_63","volume-title":"Advances in Intelligent Information Hiding and Multimedia Signal Processing","author":"M Li","year":"2021","unstructured":"Li, M., Hu, J., Ryu, K.H.: An efficient tool for semantic biomedical document analysis. In: Pan, J.-S., Li, J., Ryu, K.H., Meng, Z., Klasnja-Milicevic, A. (eds.) Advances in Intelligent Information Hiding and Multimedia Signal Processing. SIST, vol. 212, pp. 514\u2013522. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-33-6757-9_63"},{"issue":"3","key":"17_CR2","doi-asserted-by":"publisher","first-page":"834","DOI":"10.3390\/app10030834","volume":"10","author":"E Batbaatar","year":"2020","unstructured":"Batbaatar, E., Pham, V.H., Ryu, K.H.: Multi-task topic analysis framework for hallmarks of cancer with weak supervision. Appl. Sci. 10(3), 834 (2020)","journal-title":"Appl. Sci."},{"issue":"4","key":"17_CR3","doi-asserted-by":"publisher","first-page":"2197","DOI":"10.3390\/ijerph18042197","volume":"18","author":"KH Park","year":"2021","unstructured":"Park, K.H., Batbaatar, E., Piao, Y., Theera-Umpon, N., Ryu, K.H.: Deep learning feature extraction approach for hematopoietic cancer subtype classification. Int. J. Environ. Res. Public Health 18(4), 2197 (2021)","journal-title":"Int. J. Environ. Res. Public Health"},{"issue":"9","key":"17_CR4","doi-asserted-by":"publisher","first-page":"1468","DOI":"10.3390\/app8091468","volume":"8","author":"T Amarbayasgalan","year":"2018","unstructured":"Amarbayasgalan, T., Jargalsaikhan, B., Ryu, K.H.: Unsupervised novelty detection using deep autoencoders with density based clustering. Appl. Sci. 8(9), 1468 (2018)","journal-title":"Appl. Sci."},{"key":"17_CR5","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space(2013). arXiv preprint arXiv:1301.3781"},{"key":"17_CR6","unstructured":"Peters, M.E., et al.: Deep contextualized word representations (2018). arXiv preprint arXiv:1802.05365"},{"key":"17_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding (2018). arXiv preprint arXiv:1810.04805"},{"key":"17_CR8","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.eswa.2019.06.068","volume":"137","author":"J Park","year":"2019","unstructured":"Park, J., Park, C., Kim, J., Cho, M., Park, S.: ADC: advanced document clustering using contextualized representations. Expert Syst. Appl. 137, 157\u2013166 (2019)","journal-title":"Expert Syst. Appl."},{"key":"17_CR9","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1109\/TETC.2018.2830698","volume":"9","author":"X Kong","year":"2018","unstructured":"Kong, X., Mao, M., Wang, W., Liu, J., Xu, B.: VOPRec: Vector representation learning of papers with text information and structural identity for recommendation. IEEE Trans. Emerg. Topics Comput. 9, 226\u2013237 (2018)","journal-title":"IEEE Trans. Emerg. Topics Comput."},{"issue":"1","key":"17_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40535-018-0048-7","volume":"5","author":"X Luo","year":"2018","unstructured":"Luo, X., Shah, S.: Concept embedding-based weighting scheme for biomedical text clustering and visualization. Appl. Inf. 5(1), 1\u201319 (2018)","journal-title":"Appl. Inf."},{"issue":"4","key":"17_CR11","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1093\/bioinformatics\/btz682","volume":"36","author":"J Lee","year":"2020","unstructured":"Lee, J., et al.: BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics 36(4), 1234\u20131240 (2020)","journal-title":"Bioinformatics"},{"issue":"2","key":"17_CR12","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1016\/S0031-3203(02)00060-2","volume":"36","author":"A Likas","year":"2003","unstructured":"Likas, A., Vlassis, N., Verbeek, J.J.: The global k-means clustering algorithm. Pattern Recogn. 36(2), 451\u2013461 (2003)","journal-title":"Pattern Recogn."},{"key":"17_CR13","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1007\/978-0-387-30164-8_289","volume-title":"Encyclopedia of Machine Learning","author":"J Langford","year":"2010","unstructured":"Langford, J., et al.: Expectation maximization clustering. In: Sammut, Claude, Webb, Geoffrey I. (eds.) Encyclopedia of Machine Learning, pp. 382\u2013383. Springer US, Boston, MA (2010). https:\/\/doi.org\/10.1007\/978-0-387-30164-8_289"},{"key":"17_CR14","series-title":"Algorithms for Intelligent Systems","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-981-33-4191-3_2","volume-title":"Evolutionary Data Clustering: Algorithms and Applications","author":"I Aljarah","year":"2021","unstructured":"Aljarah, I., Habib, M., Nujoom, R., Faris, H., Mirjalili, S.: A comprehensive review of evaluation and fitness measures for evolutionary data clustering. In: Aljarah, I., Faris, H., Mirjalili, S. (eds.) Evolutionary Data Clustering: Algorithms and Applications. AIS, pp. 23\u201371. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-33-4191-3_2"},{"issue":"9","key":"17_CR15","doi-asserted-by":"publisher","first-page":"3307","DOI":"10.3390\/app10093307","volume":"10","author":"K Davagdorj","year":"2020","unstructured":"Davagdorj, K., Lee, J.S., Pham, V.H., Ryu, K.H.: A comparative analysis of machine learning methods for class imbalance in a smoking cessation intervention. Appl. Sci. 10(9), 3307 (2020)","journal-title":"Appl. Sci."}],"container-title":["Lecture Notes in Electrical Engineering","Genetic and Evolutionary Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-8430-2_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T09:24:34Z","timestamp":1700040274000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-8430-2_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811684296","9789811684302"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-8430-2_17","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICGEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Genetic and Evolutionary Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jilin City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icgec2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}