{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T14:28:58Z","timestamp":1742999338334,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031368219"},{"type":"electronic","value":"9783031368226"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-36822-6_8","type":"book-chapter","created":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T03:25:54Z","timestamp":1689305154000},"page":"93-104","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Named Entity Recognition for\u00a0Nepali Using BERT Based Models"],"prefix":"10.1007","author":[{"given":"Bishal Debb","family":"Pande","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aman","family":"Shakya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanjeeb Prasad","family":"Panday","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Basanta","family":"Joshi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,15]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"21","DOI":"10.4236\/iim.2014.62004","volume":"06","author":"S Bam","year":"2014","unstructured":"Bam, S., Shahi, T.: Named entity recognition for Nepali text using support vector machines. Intell. Inf. Manage. 06, 21\u201329 (2014). https:\/\/doi.org\/10.4236\/iim.2014.62004","journal-title":"Intell. Inf. Manage."},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information (2016)","DOI":"10.1162\/tacl_a_00051"},{"key":"8_CR3","doi-asserted-by":"publisher","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale (2019). https:\/\/doi.org\/10.48550\/ARXIV.1911.02116, https:\/\/arxiv.org\/abs\/1911.02116","DOI":"10.48550\/ARXIV.1911.02116"},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Cui, Y., Jia, M., Lin, T., Song, Y., Belongie, S.J.: Class-balanced loss based on effective number of samples. CoRR abs\/1901.05555 (2019). http:\/\/arxiv.org\/abs\/1901.05555","DOI":"10.1109\/CVPR.2019.00949"},{"key":"8_CR5","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding (2019)"},{"key":"8_CR6","doi-asserted-by":"publisher","first-page":"31","DOI":"10.5120\/14607-2859","volume":"84","author":"A Dey","year":"2013","unstructured":"Dey, A., Prukayastha, B.: Named entity recognition using gazetteer method and n-gram technique for an inflectional language: a hybrid approach. Int. J. Comput. Appl. 84, 31\u201335 (2013). https:\/\/doi.org\/10.5120\/14607-2859","journal-title":"Int. J. Comput. Appl."},{"key":"8_CR7","doi-asserted-by":"publisher","unstructured":"Grishman, R., Sundheim, B.: Message understanding conference-6: a brief history. In: Proceedings of the 16th Conference on Computational Linguistics, COLING 1996, vol. 1, pp. 466\u2013471. Association for Computational Linguistics, USA (1996). https:\/\/doi.org\/10.3115\/992628.992709","DOI":"10.3115\/992628.992709"},{"issue":"4","key":"8_CR8","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/5254.708428","volume":"13","author":"M Hearst","year":"1998","unstructured":"Hearst, M., Dumais, S., Osuna, E., Platt, J., Scholkopf, B.: Support vector machines. IEEE Intell. Syst. Appl. 13(4), 18\u201328 (1998). https:\/\/doi.org\/10.1109\/5254.708428","journal-title":"IEEE Intell. Syst. Appl."},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Kakwani, D., et al.: IndicNLPSuite: monolingual corpora, evaluation benchmarks and pre-trained multilingual language models for Indian languages. In: Findings of EMNLP (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.445"},{"key":"8_CR10","doi-asserted-by":"publisher","unstructured":"Koirala, P., Niraula, N.B.: NPVec1: word embeddings for Nepali - construction and evaluation. In: Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021), pp. 174\u2013184. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.repl4nlp-1.18, https:\/\/aclanthology.org\/2021.repl4nlp-1.18","DOI":"10.18653\/v1\/2021.repl4nlp-1.18"},{"key":"8_CR11","unstructured":"Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the Eighteenth International Conference on Machine Learning, ICML 2001, pp. 282\u2013289. Morgan Kaufmann Publishers Inc., San Francisco (2001)"},{"issue":"1","key":"8_CR12","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TKDE.2020.2981314","volume":"34","author":"J Li","year":"2020","unstructured":"Li, J., Sun, A., Han, J., Li, C.: A survey on deep learning for named entity recognition. IEEE Trans. Knowl. Data Eng. 34(1), 50\u201370 (2020)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"8_CR13","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1007\/978-3-030-29750-3_6","volume-title":"Creativity in Intelligent Technologies and Data Science","author":"G Maharjan","year":"2019","unstructured":"Maharjan, G., Bal, B.K., Regmi, S.: Named entity recognition (NER) for Nepali. In: Kravets, A.G., Groumpos, P.P., Shcherbakov, M., Kultsova, M. (eds.) CIT &DS 2019. CCIS, vol. 1084, pp. 71\u201380. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29750-3_6"},{"key":"8_CR14","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013)"},{"key":"8_CR15","doi-asserted-by":"publisher","unstructured":"Murthy, R., Bhattacharjee, P., Sharnagat, R., Khatri, J., Kanojia, D., Bhattacharyya, P.: HiNER: a large Hindi named entity recognition dataset (2022). https:\/\/doi.org\/10.48550\/ARXIV.2204.13743, https:\/\/arxiv.org\/abs\/2204.13743","DOI":"10.48550\/ARXIV.2204.13743"},{"key":"8_CR16","unstructured":"Nakayama, H.: SeqEval: a python framework for sequence labeling evaluation (2018). https:\/\/github.com\/chakki-works\/seqeval"},{"key":"8_CR17","doi-asserted-by":"publisher","unstructured":"Niraula, N., Chapagain, J.: Named entity recognition for Nepali: data sets and algorithms. In: The International FLAIRS Conference Proceedings, vol. 35 (2022). https:\/\/doi.org\/10.32473\/flairs.v35i.130725","DOI":"10.32473\/flairs.v35i.130725"},{"key":"8_CR18","doi-asserted-by":"publisher","unstructured":"Pennington, J., Socher, R., Manning, C.: GloVe: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543. Association for Computational Linguistics, Doha (2014). https:\/\/doi.org\/10.3115\/v1\/D14-1162, https:\/\/www.aclweb.org\/anthology\/D14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"8_CR19","doi-asserted-by":"crossref","unstructured":"Rau, L.F.: Extracting company names from text. In: 1991 Proceedings of the Seventh IEEE Conference on Artificial Intelligence Application, vol. i, pp. 29\u201332 (1991)","DOI":"10.1109\/CAIA.1991.120841"},{"key":"8_CR20","doi-asserted-by":"publisher","unstructured":"Ruokolainen, T., Kauppinen, P., Silfverberg, M., Lind\u00e9n, K.: A finnish news corpus for named entity recognition. Lang. Resour. Eval. 54(1), 247\u2013272 (2019). https:\/\/doi.org\/10.1007\/s10579-019-09471-7","DOI":"10.1007\/s10579-019-09471-7"},{"key":"8_CR21","doi-asserted-by":"publisher","unstructured":"Singh, O.M., Padia, A., Joshi, A.: Named entity recognition for Nepali language. In: 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC), pp. 184\u2013190 (2019). https:\/\/doi.org\/10.1109\/CIC48465.2019.00031","DOI":"10.1109\/CIC48465.2019.00031"},{"key":"8_CR22","unstructured":"Vaswani, A., et al.: Attention is all you need (2017)"}],"container-title":["Lecture Notes in Computer Science","Advances and Trends in Artificial Intelligence. Theory and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-36822-6_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T03:39:51Z","timestamp":1729741191000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-36822-6_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031368219","9783031368226"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-36822-6_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"15 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IEA\/AIE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"36","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ieaaie2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ieaaie2023.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"129","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}