{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T15:23:41Z","timestamp":1777562621928,"version":"3.51.4"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031353192","type":"print"},{"value":"9783031353208","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\/978-3-031-35320-8_29","type":"book-chapter","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T05:01:53Z","timestamp":1686632513000},"page":"404-415","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Effective Information Retrieval, Question Answering and\u00a0Abstractive Summarization on\u00a0Large-Scale Biomedical Document Corpora"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2326-1284","authenticated-orcid":false,"given":"Naveen","family":"Shenoy","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2586-3641","authenticated-orcid":false,"given":"Pratham","family":"Nayak","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3434-8234","authenticated-orcid":false,"given":"Sarthak","family":"Jain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0888-7238","authenticated-orcid":false,"given":"S.","family":"Sowmya Kamath","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2557-3182","authenticated-orcid":false,"given":"Vijayan","family":"Sugumaran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,14]]},"reference":[{"key":"29_CR1","doi-asserted-by":"crossref","unstructured":"Bachina, S., Balumuri, S., Kamath, S.: Ensemble ALBERT and RoBERTa for span prediction in question answering. In: Proceedings of 59th Annual Meeting of the Association for Computational Linguistics and 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), pp. 63\u201368 (2021)","DOI":"10.18653\/v1\/2021.dialdoc-1.9"},{"key":"29_CR2","doi-asserted-by":"crossref","unstructured":"Beltagy, I., Lo, K., Cohan, A.: Scibert: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676 (2019)","DOI":"10.18653\/v1\/D19-1371"},{"key":"29_CR3","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/978-3-030-93080-6_11","volume-title":"AI for Disease Surveillance and Pandemic Intelligence","author":"P Bhatia","year":"2021","unstructured":"Bhatia, P., et al.: AWS CORD-19 search: a neural search engine for COVID-19 literature. In: Shaban-Nejad, A., Michalowski, M., Bianco, S. (eds.) W3PHAI 2021. SCI, vol. 1013, pp. 131\u2013145. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-93080-6_11"},{"key":"29_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1007\/978-3-319-72413-3_10","volume-title":"Big Data Analytics","author":"AP Bhopale","year":"2017","unstructured":"Bhopale, A.P., Shevgoor, S.K.: Temporal topic modeling of scholarly publications for future trend forecasting. In: Reddy, P.K., Sureka, A., Chakravarthy, S., Bhalla, S. (eds.) BDA 2017. LNCS, vol. 10721, pp. 144\u2013163. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-72413-3_10"},{"key":"29_CR5","unstructured":"Canese, K., Weis, S.: Pubmed: the bibliographic database. The NCBI handbook, vol. 2(1) (2013)"},{"key":"29_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Q., Peng, Y., Lu, Z.: Biosentvec: creating sentence embeddings for biomedical texts. In: 2019 IEEE International Conference on Healthcare Informatics, pp. 1\u20135. IEEE (2019)","DOI":"10.1109\/ICHI.2019.8904728"},{"key":"29_CR7","unstructured":"Das, D., et al.: Information retrieval and extraction on COVID-19 clinical articles using graph community detection and bio-Bert embeddings. In: Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020 (2020)"},{"key":"29_CR8","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 (2018)"},{"issue":"1","key":"29_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-021-00437-0","volume":"4","author":"A Esteva","year":"2021","unstructured":"Esteva, A., et al.: COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization. NPJ Digital Med. 4(1), 1\u20139 (2021)","journal-title":"NPJ Digital Med."},{"issue":"1","key":"29_CR10","doi-asserted-by":"publisher","first-page":"160035","DOI":"10.1038\/sdata.2016.35","volume":"3","author":"AE Johnson","year":"2016","unstructured":"Johnson, A.E., et al.: Mimic-iii, a freely accessible critical care database. Sci. Data 3(1), 160035 (2016)","journal-title":"Sci. Data"},{"key":"29_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-80599-9_23","volume-title":"Natural Language Processing and Information Systems","author":"GS Krishnan","year":"2021","unstructured":"Krishnan, G.S., Sowmya Kamath, S., Sugumaran, V.: Predicting vaccine hesitancy and vaccine sentiment using topic modeling and\u00a0evolutionary optimization. In: M\u00e9tais, E., Meziane, F., Horacek, H., Kapetanios, E. (eds.) NLDB 2021. LNCS, vol. 12801, pp. 255\u2013263. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-80599-9_23"},{"issue":"4","key":"29_CR12","doi-asserted-by":"publisher","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"},{"key":"29_CR13","doi-asserted-by":"crossref","unstructured":"Luan, Y., He, L., Ostendorf, M., Hajishirzi, H.: Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction. arXiv preprint arXiv:1808.09602 (2018)","DOI":"10.18653\/v1\/D18-1360"},{"key":"29_CR14","unstructured":"Nguyen, T., et al.: MS MARCO: a human generated machine reading comprehension dataset. In: CoCo@ NIPs (2016)"},{"key":"29_CR15","doi-asserted-by":"crossref","unstructured":"Nogueira, R., Jiang, Z., Lin, J.: Document ranking with a pretrained sequence-to-sequence model. arXiv preprint arXiv:2003.06713 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.63"},{"issue":"140","key":"29_CR16","first-page":"1","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21(140), 1\u201367 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"29_CR17","doi-asserted-by":"crossref","unstructured":"Rajpurkar, P., Zhang, J., Lopyrev, K., Liang, P.: Squad: 100,000+ questions for machine comprehension of text. arXiv preprint arXiv:1606.05250 (2016)","DOI":"10.18653\/v1\/D16-1264"},{"key":"29_CR18","doi-asserted-by":"crossref","unstructured":"Robertson, S.E., Walker, S., Beaulieu, M., Gatford, M., Payne, A.: Okapi at TREC-4. Nist Special Publication Sp pp. 73\u201396 (1996)","DOI":"10.6028\/NIST.SP.500-236.routing-city"},{"key":"29_CR19","unstructured":"Tang, R., et al.: Rapidly bootstrapping a question answering dataset for COVID-19. arXiv preprint arXiv:2004.11339 (2020)"},{"issue":"1","key":"29_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12859-015-0564-6","volume":"16","author":"G Tsatsaronis","year":"2015","unstructured":"Tsatsaronis, G., et al.: An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition. BMC Bioinform. 16(1), 1\u201328 (2015)","journal-title":"BMC Bioinform."},{"key":"29_CR21","doi-asserted-by":"crossref","unstructured":"Upadhya, B.A., Udupa, S.: Deep neural network models for question classification in community question-answering forums. In: 2019 10th International Conference on Computing, Communication and Networking Technologies. IEEE (2019)","DOI":"10.1109\/ICCCNT45670.2019.8944861"},{"key":"29_CR22","unstructured":"Wang, L.L., Lo, K., Chandrasekhar, Y., Reas, R., Yang, J., et al.: Cord-19: The covid-19 open research dataset (2020)"},{"key":"29_CR23","doi-asserted-by":"crossref","unstructured":"Xing, W., Ghorbani, A.: Weighted pagerank algorithm. In: Proceedings. Second Annual Conference on Communication Networks and Services Research, 2004, pp. 305\u2013314. IEEE (2004)","DOI":"10.1109\/DNSR.2004.1344743"},{"key":"29_CR24","doi-asserted-by":"publisher","unstructured":"Zhang, E., Gupta, N., Tang, R., Han, X., Pradeep, R., et al.: Covidex: neural ranking models and keyword search infrastructure for the COVID-19 open research dataset (2020). https:\/\/doi.org\/10.48550\/ARXIV.2007.07846","DOI":"10.48550\/ARXIV.2007.07846"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-35320-8_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T04:58:12Z","timestamp":1729573092000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-35320-8_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031353192","9783031353208"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-35320-8_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"14 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Derby","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"21 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.derby.ac.uk\/events\/latest-events\/nldb-2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"89","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":"31","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":"14","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":"35% - 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)"}}]}}