{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T11:51:44Z","timestamp":1769169104064,"version":"3.49.0"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031274084","type":"print"},{"value":"9783031274091","type":"electronic"}],"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\/978-3-031-27409-1_80","type":"book-chapter","created":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T12:02:53Z","timestamp":1684929773000},"page":"872-880","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Toxic Comment Classification"],"prefix":"10.1007","author":[{"given":"B.","family":"Naseeba","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pothuri Hemanth Raga","family":"Sai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. Venkata Phani","family":"Karthik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengamma","family":"Chitteti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katari","family":"Sai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J.","family":"Avanija","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,25]]},"reference":[{"key":"80_CR1","unstructured":"Guggilla, C., Miller, T., Gurevych, I.: CNN-and LSTM-based claim classification in online user comments. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 2740\u20132751 (2016)"},{"issue":"6","key":"80_CR2","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.3390\/app9061123","volume":"9","author":"M Jabreel","year":"2019","unstructured":"Jabreel, M., Moreno, A.: A deep learning-based approach for multi-label emotion classification in tweets. Appl. Sci. 9(6), 1123 (2019)","journal-title":"Appl. Sci."},{"key":"80_CR3","doi-asserted-by":"crossref","unstructured":"Haralabopoulos, Anagnostopoulos, I., & McAuley, D.: Ensemble deep learning for multilabel binary classification of user-generated content. Algorithms 13(4), 83 (2020)","DOI":"10.3390\/a13040083"},{"key":"80_CR4","doi-asserted-by":"crossref","unstructured":"Sridharan, M., Swapna, T.R.: Amrita School of Engineering-CSEatSemEval-2019 Task 6: Manipulating attention with temporal convolutional neural network for offense identification and classification. In: Proceedings of the 13th International Workshop on Semantic Evaluation, pp. 540\u2013546 (2019)","DOI":"10.18653\/v1\/S19-2097"},{"key":"80_CR5","doi-asserted-by":"crossref","unstructured":"Mozafari, M., Farahbakhsh, R., Crespi, N.: A BERT-based transfer learning approach for hate speech detection in online social media. In: International Conference on Complex Networks and Their Applications, pp. 928\u2013940. Springer, Cham (2019)","DOI":"10.1007\/978-3-030-36687-2_77"},{"key":"80_CR6","doi-asserted-by":"crossref","unstructured":"Liang, J., Meyerson, E., Hodjat, B., Fink, D., Mutch, K., Miikkulainen, R.: Evolutionary neural automl for deep learning. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 401\u2013409 (2019)","DOI":"10.1145\/3321707.3321721"},{"key":"80_CR7","doi-asserted-by":"crossref","unstructured":"Kajla, H., Hooda, J., Saini, G.: Classification of online toxic comments using machine learning algorithms. In: 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1119\u20131123 (2020). IEEE","DOI":"10.1109\/ICICCS48265.2020.9120939"},{"key":"80_CR8","doi-asserted-by":"crossref","unstructured":"Feurer, M., Hutter, F.: Hyperparameter optimization. In: Automated Machine Learning (pp. 3\u201333). Springer, Cham. Zhang, X., Liao, Q., Kang, Z., Liu, B., Ou, Y., Du, J., ... & Fang, Z.: Self-healing originated van der Waals homojunction with strong interlayer coupling for high-performance photodiodes. ACS Nano, 13(3), 3280\u20133291 (2019)","DOI":"10.1021\/acsnano.8b09130"},{"key":"80_CR9","doi-asserted-by":"crossref","unstructured":"Tabassi, E., Burns, K.J., Hadjimichael, M., Molina-Markham, A.D., Sexton, J.T.: A Taxonomy and Terminology of Adversarial Machine Learning, (2019)","DOI":"10.6028\/NIST.IR.8269-draft"},{"issue":"1","key":"80_CR10","doi-asserted-by":"publisher","first-page":"423","DOI":"10.32604\/iasc.2022.024757","volume":"34","author":"G Sunitha","year":"2022","unstructured":"Sunitha, G., et al.: Modeling of chaotic political optimizer for crop yield prediction. Intelligent Automation and Soft Computing 34(1), 423\u2013437 (2022)","journal-title":"Intelligent Automation and Soft Computing"},{"key":"80_CR11","doi-asserted-by":"crossref","unstructured":"Sunitha, G., Arunachalam, R., Abd\u2010Elnaby, M., Eid, M.M., Rashed, A.N.Z.: A comparative analysis of deep neural network architectures for the dynamic diagnosis of COVID\u201019 based on acoustic cough features. Int. J. Imaging Systems Tech. (2022)","DOI":"10.1002\/ima.22749"},{"issue":"2","key":"80_CR12","first-page":"2134","volume":"12","author":"C Karthikeyan","year":"2021","unstructured":"Karthikeyan, C., Sunitha, G., Avanija, J., Reddy Madhavi, K., Madhan, E.S.: Prediction of climate change using SVM and na\u00efve bayes machine learning algorithms. Turkish Journal of Computer and Mathematics Education 12(2), 2134\u20132139 (2021)","journal-title":"Turkish Journal of Computer and Mathematics Education"},{"key":"80_CR13","doi-asserted-by":"crossref","unstructured":"Abbagalla, S., Rupa Devi, B., Anjaiah, P., Reddy Madhavi, K.: \u201cAnalysis of COVID-19-impacted zone using machine learning algorithms\u201d. Springer series \u2013 Lecture Notes on Data Engineering and Communication Technology, Vol.63, 621\u2013627 (2021)","DOI":"10.1007\/978-981-16-0081-4_62"},{"key":"80_CR14","doi-asserted-by":"publisher","unstructured":"Avanija, J., Sunitha, G., Hittesh Sai Vittal, R.: \u201cDengue outbreak prediction using regression model in chittoor district, Andhra Pradesh, India.\u201d Int. J. Recent Tech. Engineer. 8(4), 10057\u201310060 (2019). doi: https:\/\/doi.org\/10.35940\/ijrte.d9519.118419","DOI":"10.35940\/ijrte.d9519.118419"},{"key":"80_CR15","unstructured":"Reddy Madhavi, K., et al.: \u201cCOVID-19 detection using deep learning\u201d, In: 20th International Conference on Hybrid Intelligent Systems-HIS 2020, at Machine Intelligence Research (MIR) labs, USA, Springer AISC, 1375, pp 1\u20137 (2020)"},{"key":"80_CR16","doi-asserted-by":"publisher","unstructured":"Kora, P., Rajani, A., Chinnaiah, M.C., Madhavi, R. Swaraja, K., Kollati, M.: EEG-Based brain-electric activity detection during meditation using spectral estimation techniques. pp. 687\u2013693 (2021) doi: https:\/\/doi.org\/10.1007\/978-981-16-1941-0_68","DOI":"10.1007\/978-981-16-1941-0_68"},{"key":"80_CR17","doi-asserted-by":"crossref","unstructured":"Prabhakar, T., Srujan Raju, K., Reddy Madhavi, K.: Support vector machine classification of remote sensing images with the wavelet-based statistical features. In: Fifth International Conference on Smart Computing and Informatics (SCI 2021), Smart Intelligent Computing and Applications, Volume 2. Smart Innovation, Systems and Technologies, vol 283. Springer, Singapore (2022)","DOI":"10.1007\/978-981-16-9705-0_59"},{"key":"80_CR18","doi-asserted-by":"publisher","unstructured":"Rajani, A., Kora, P., Madhavi, R. Jangaraj, A.: Quality improvement of retinal optical coherence tomography. 1\u20135 (2021) https:\/\/doi.org\/10.1109\/INCET51464.2021.9456151","DOI":"10.1109\/INCET51464.2021.9456151"},{"key":"80_CR19","doi-asserted-by":"publisher","unstructured":"Reddy Madhavi, K., Madhavi, G., Rupa Devi, B., Kora, P.: \u201cDetection of pneumonia using deep transfer learning architectures\u201d, Int. J. Advanced Trends Computer Sci. Engineer. 9(5), pp. 8934- 8937 (2020). ISSN 2278-3091 https:\/\/doi.org\/10.30534\/ijatcse\/2020\/292952020","DOI":"10.30534\/ijatcse\/2020\/292952020"}],"container-title":["Lecture Notes in Networks and Systems","Hybrid Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-27409-1_80","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:43:08Z","timestamp":1729471388000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-27409-1_80"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031274084","9783031274091"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-27409-1_80","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"25 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Hybrid Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"his2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/his22\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}