{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,28]],"date-time":"2025-12-28T15:16:07Z","timestamp":1766934967844,"version":"3.28.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,17]]},"DOI":"10.1109\/bigdata55660.2022.10020825","type":"proceedings-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T19:35:23Z","timestamp":1674761723000},"page":"4737-4745","source":"Crossref","is-referenced-by-count":7,"title":["Fine-Tuning BERT-based Language Models for Duplicate Trouble Report Retrieval"],"prefix":"10.1109","author":[{"given":"Nathan","family":"Bosch","sequence":"first","affiliation":[{"name":"Ericsson AB,GFTL GAIA,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Serveh","family":"Shalmashi","sequence":"additional","affiliation":[{"name":"Ericsson AB,GFTL GAIA,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Forough","family":"Yaghoubi","sequence":"additional","affiliation":[{"name":"Ericsson AB,GFTL GAIA,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Henrik","family":"Holm","sequence":"additional","affiliation":[{"name":"Ericsson AB,GFTL GAIA,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fitsum","family":"Gaim","sequence":"additional","affiliation":[{"name":"Ericsson AB,GFTL GAIA,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir H.","family":"Payberah","sequence":"additional","affiliation":[{"name":"KTH Royal Institute of Technology,Stockholm,Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.3384\/diss.diva-147059"},{"year":"2022","author":"Bosch","article-title":"Integrating telecommunications-specific language models into a trouble report retrieval approach","key":"ref2"},{"year":"2021","author":"Marzo i Grimalt","article-title":"Natural language processing model for log analysis to retrieve solutions for troubleshooting processes","key":"ref3"},{"key":"ref4","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv preprint arXiv:1810.04805"},{"key":"ref5","article-title":"Ms marco: A human generated machine reading comprehension dataset","author":"Bajaj","year":"2016","journal-title":"arXiv preprint arXiv:1611.09268"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1561\/1500000019"},{"year":"2021","author":"Holm","article-title":"Bidirectional encoder representations from transformers (bert) for question answering in the telecom domain.: Adapting a bert-like language model to the telecom domain using the electra pre-training approach","key":"ref7"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.18653\/v1\/n19-5004"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1016\/s0079-7421(08)60536-8"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1016\/S1364-6613(99)01294-2"},{"key":"ref11","article-title":"An empirical investigation of catastrophic forgetting in gradient-based neural networks","author":"Goodfellow","year":"2013","journal-title":"arXiv preprint arXiv:1312.6211"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1073\/pnas.1611835114"},{"year":"2022","author":"Grimalt","article-title":"Berticsson: A recommender system for troubleshooting","key":"ref13"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.2200\/s01123ed1v01y202108hlt053"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1016\/j.ipm.2019.102067"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.18653\/v1\/D19-1410"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1007\/978-1-0716-0826-5_3"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"ref19","article-title":"Approximate nearest neighbor negative contrastive learning for dense text retrieval","author":"Xiong","year":"2020","journal-title":"arXiv preprint arXiv:2007.00808"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.18653\/v1\/P19-1612"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1145\/3132847.3132914"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1145\/3159652.3159659"},{"key":"ref23","article-title":"Multi-stage document ranking with bert","author":"Nogueira","year":"2019","journal-title":"arXiv preprint arXiv:1910.14424"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1145\/3397271.3401075"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1109\/TKDE.2009.191"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.18653\/v1\/2020.acl-main.740"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1037\/0033-295x.97.2.285"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.18653\/v1\/P18-1031"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1007\/978-3-030-32381-3_16"},{"key":"ref30","first-page":"3987","article-title":"Continual learning through synaptic intelligence","volume-title":"International Conference on Machine Learning","author":"Zenke"},{"key":"ref31","article-title":"Gradient episodic memory for continual learning","volume":"30","author":"Lopez-Paz","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref32","article-title":"Revisiting natural gradient for deep networks","author":"Pascanu","year":"2013","journal-title":"arXiv preprint arXiv:1301.3584"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/IJCNN48605.2020.9206891"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1007\/978-3-030-72113-8_25"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.18653\/v1\/2021.eacl-main.82"},{"key":"ref36","article-title":"Roberta: A robustly optimized bert pretraining approach","author":"Liu","year":"2019","journal-title":"arXiv preprint arXiv:1907.11692"},{"key":"ref37","first-page":"77","article-title":"The trec-8 question answering track report","volume":"99","author":"Voorhees","year":"1999","journal-title":"Trec"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.2200\/S00368ED1V01Y201105ICR019"}],"event":{"name":"2022 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2022,12,17]]},"location":"Osaka, Japan","end":{"date-parts":[[2022,12,20]]}},"container-title":["2022 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10020192\/10020156\/10020825.pdf?arnumber=10020825","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T06:07:03Z","timestamp":1707804423000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10020825\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,17]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/bigdata55660.2022.10020825","relation":{},"subject":[],"published":{"date-parts":[[2022,12,17]]}}}