{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T11:51:36Z","timestamp":1781956296289,"version":"3.54.5"},"reference-count":49,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100010240","name":"National Planning Office of Philosophy and Social Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010240","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing &amp; Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104788","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T14:07:28Z","timestamp":1776348448000},"page":"104788","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["A Domain-Adapted Pipeline for Structured Information Extraction from Police Incident Announcements on Social Media"],"prefix":"10.1016","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3186-3895","authenticated-orcid":false,"given":"Mengfan","family":"Shen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangqi","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xindi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqiang","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.ipm.2026.104788_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104262","article-title":"Large language models for scholarly ontology generation: An extensive analysis in the engineering field","volume":"63","author":"Aggarwal","year":"2026","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104788_bib0002","series-title":"2016 IEEE\/WIC\/ACM International Conference on Web Intelligence (WI)","first-page":"526","article-title":"Mining social Media content for crime prediction","author":"Aghababaei","year":"2016"},{"key":"10.1016\/j.ipm.2026.104788_bib0003","article-title":"Scaling up with integrity: Valid and efficient narrative policy framework analyses using large language models","author":"Anglin","year":"2025","journal-title":"Policy Studies Journal"},{"key":"10.1016\/j.ipm.2026.104788_bib0004","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.ins.2019.01.023","article-title":"An efficient recommendation generation using relevant Jaccard similarity","volume":"483","author":"Bag","year":"2019","journal-title":"Information Sciences"},{"issue":"1","key":"10.1016\/j.ipm.2026.104788_bib0005","first-page":"54","article-title":"A new inventory of 30 terrorism databases and data sets","volume":"14","author":"Bowie","year":"2020","journal-title":"Perspectives on Terrorism"},{"issue":"3","key":"10.1016\/j.ipm.2026.104788_bib0006","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/s11292-019-09372-3","article-title":"Hot spots policing and crime reduction: An update of an ongoing systematic review and meta-analysis","volume":"15","author":"Braga","year":"2019","journal-title":"Journal of Experimental Criminology"},{"key":"10.1016\/j.ipm.2026.104788_bib0007","doi-asserted-by":"crossref","unstructured":"Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Aletras, N., & Androutsopoulos, I. (2020). LEGAL-BERT: The muppets straight out of law school. arXiv Preprint arXiv:2010.02559.","DOI":"10.18653\/v1\/2020.findings-emnlp.261"},{"issue":"6","key":"10.1016\/j.ipm.2026.104788_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104278","article-title":"MedScaleRE-PF: A prompt-based framework with retrieval-augmented generation, chain-of-thought, and self-verification for scale-specific relation extraction in Chinese medical literature","volume":"62","author":"Chen","year":"2025","journal-title":"Information Processing & Management"},{"issue":"141","key":"10.1016\/j.ipm.2026.104788_bib0009","doi-asserted-by":"crossref","DOI":"10.1098\/rsif.2017.0387","article-title":"Opportunities and obstacles for deep learning in biology and medicine","volume":"15","author":"Ching","year":"2018","journal-title":"Journal of the Royal Society Interface"},{"key":"10.1016\/j.ipm.2026.104788_bib0010","series-title":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","first-page":"827","article-title":"Rule-based information extraction is dead! long live rule-based information extraction systems!","author":"Chiticariu","year":"2013"},{"issue":"1","key":"10.1016\/j.ipm.2026.104788_bib0011","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1038\/s41467-024-45563-x","article-title":"Structured information extraction from scientific text with large language models","volume":"15","author":"Dagdelen","year":"2024","journal-title":"Nature Communications"},{"issue":"4","key":"10.1016\/j.ipm.2026.104788_bib0012","doi-asserted-by":"crossref","first-page":"4975","DOI":"10.1109\/TCSS.2023.3259480","article-title":"AI-assisted deep NLP-based approach for prediction of fake news from social Media users","volume":"11","author":"Devarajan","year":"2023","journal-title":"IEEE Transactions on Computational Social Systems"},{"key":"10.1016\/j.ipm.2026.104788_bib0013","series-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","first-page":"4171","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","volume":"1","author":"Devlin","year":"2019"},{"key":"10.1016\/j.ipm.2026.104788_bib0014","first-page":"4","article-title":"Crime places in crime theory","author":"Eck","year":"2015","journal-title":"Crime and Place: Crime Prevention Studies"},{"key":"10.1016\/j.ipm.2026.104788_bib0015","series-title":"The rise of big data policing","article-title":"The rise of big data policing: Surveillance, race, and the future of law enforcement","author":"Ferguson","year":"2017"},{"issue":"6","key":"10.1016\/j.ipm.2026.104788_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104227","article-title":"Augmented graph information bottleneck with type-aware periodicity heterogeneity for explainable crime prediction","volume":"62","author":"Fu","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104788_bib0017","unstructured":"Guo, D., Yang, D., Zhang, H., Song, J., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., & others. (2025). Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning. arXiv Preprint arXiv:2501.12948."},{"key":"10.1016\/j.ipm.2026.104788_bib0019","unstructured":"Han, Z., Gao, C., Liu, J., Zhang, J., & Zhang, S.Q. (2024). Parameter-efficient fine-tuning for large models: A comprehensive survey. arXiv Preprint arXiv:2403.14608."},{"key":"10.1016\/j.ipm.2026.104788_bib0018","series-title":"Instruction tuned models are quick learners with instruction equipped data on downstream tasks","author":"Gupta","year":"2023"},{"key":"10.1016\/j.ipm.2026.104788_bib0020","series-title":"International Conference on Machine Learning","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","author":"Houlsby","year":"2019"},{"key":"10.1016\/j.ipm.2026.104788_bib0021","doi-asserted-by":"crossref","first-page":"328","DOI":"10.18653\/v1\/P18-1031","article-title":"Universal language model fine-tuning for text classification","volume":"1","author":"Howard","year":"2018","journal-title":"Proceedings of the 56th annual meeting of the association for computational linguistics"},{"issue":"2","key":"10.1016\/j.ipm.2026.104788_bib0022","first-page":"3","article-title":"Lora: Low-rank adaptation of large language models","volume":"1","author":"Hu","year":"2022","journal-title":"ICLR"},{"key":"10.1016\/j.ipm.2026.104788_bib0023","series-title":"Contemporary terrorism studies","first-page":"113","article-title":"Terrorism open source databases","author":"LaFree","year":"2022"},{"key":"10.1016\/j.ipm.2026.104788_bib0024","doi-asserted-by":"crossref","unstructured":"Lester, B., Al-Rfou, R., & Constant, N. (2021). The power of scale for parameter-efficient prompt tuning. arXiv Preprint arXiv:2104.08691.","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"10.1016\/j.ipm.2026.104788_bib0025","series-title":"International Conference on Intelligent Data Engineering and Automated Learning","first-page":"611","article-title":"Distance weighted cosine similarity measure for text classification","author":"Li","year":"2013"},{"key":"10.1016\/j.ipm.2026.104788_bib0026","first-page":"74","article-title":"Rouge: A package for automatic evaluation of summaries","author":"Lin","year":"2004","journal-title":"Text Summarization Branches Out"},{"issue":"9","key":"10.1016\/j.ipm.2026.104788_bib0027","first-page":"1","article-title":"Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing","volume":"55","author":"Liu","year":"2023","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.ipm.2026.104788_bib0028","series-title":"Natural language analytics with generative large-language models","author":"Marcondes","year":"2025"},{"key":"10.1016\/j.ipm.2026.104788_bib0029","series-title":"2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL)","first-page":"70","article-title":"Social Media analysis for Criminal behavior detection: Methods, application and challenge","author":"Patel","year":"2025"},{"key":"10.1016\/j.ipm.2026.104788_bib0030","doi-asserted-by":"crossref","unstructured":"Prathap, B., Krishna, A.V.N., & Balachandran, K. (2021). Crime analysis and forecasting on Spatio temporal news feed data\u2014An Indian context. 307\u2013327. https:\/\/doi.org\/10.1007\/978-3-030-74575-2_16.","DOI":"10.1007\/978-3-030-74575-2_16"},{"key":"10.1016\/j.ipm.2026.104788_bib0031","author":"Radford","year":"2018","journal-title":"Improving language understanding by generative pre-training"},{"issue":"140","key":"10.1016\/j.ipm.2026.104788_bib0032","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"Journal of Machine Learning Research"},{"issue":"3","key":"10.1016\/j.ipm.2026.104788_bib0033","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1162\/coli_a_00322","article-title":"A structured review of the validity of BLEU","volume":"44","author":"Reiter","year":"2018","journal-title":"Computational Linguistics"},{"key":"10.1016\/j.ipm.2026.104788_bib0034","series-title":"Understanding crime statistics: Revisiting the divergence of the ncvs and ucr","first-page":"340","article-title":"Book review","author":"Roberts","year":"2010"},{"key":"10.1016\/j.ipm.2026.104788_bib0035","doi-asserted-by":"crossref","first-page":"95456","DOI":"10.1109\/ACCESS.2021.3094532","article-title":"Adaptable reduced-complexity approach based on State vector machine for identification of criminal activists on social Media","volume":"9","author":"Shafi","year":"2021","journal-title":"IEEE access : Practical innovations, open solutions"},{"key":"10.1016\/j.ipm.2026.104788_bib0036","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph20031862","article-title":"Extracting useful emergency information from Social Media: A method integrating machine learning and rule-based classification","volume":"20","author":"Shen","year":"2023","journal-title":"International Journal of Environmental Research and Public Health"},{"key":"10.1016\/j.ipm.2026.104788_bib0037","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.apgeog.2016.02.008","article-title":"Street profile analysis: A new method for mapping crime on major roadways","volume":"69","author":"Spicer","year":"2016","journal-title":"Applied Geography"},{"key":"10.1016\/j.ipm.2026.104788_bib0038","unstructured":"Talebirad, Y., & Nadiri, A. (2023). Multi-agent collaboration: Harnessing the power of intelligent llm agents. arXiv Preprint arXiv:2306.03314."},{"key":"10.1016\/j.ipm.2026.104788_bib0039","doi-asserted-by":"crossref","first-page":"93204","DOI":"10.1109\/ACCESS.2023.3308967","article-title":"Multimodal deep learning crime prediction using tweets","volume":"11","author":"Tam","year":"2023","journal-title":"IEEE access : Practical innovations, open solutions"},{"issue":"1","key":"10.1016\/j.ipm.2026.104788_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104286","article-title":"Language model collaboration for relation extraction from classical Chinese historical documents","volume":"63","author":"Tang","year":"2026","journal-title":"Information Processing & Management"},{"issue":"5","key":"10.1016\/j.ipm.2026.104788_bib0041","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1177\/1477370810367014","article-title":"Exploring the international decline in crime rates","volume":"7","author":"Tseloni","year":"2010","journal-title":"European Journal of Criminology"},{"issue":"1","key":"10.1016\/j.ipm.2026.104788_bib0042","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/0735648X.2022.2080100","article-title":"Police accounts of critical incidents: A descriptive and empirical assessment","volume":"47","author":"Uchida","year":"2024","journal-title":"Journal of Crime and Justice"},{"key":"10.1016\/j.ipm.2026.104788_bib0043","first-page":"30","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.ipm.2026.104788_bib0044","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2023.104834","article-title":"Cross-domain car detection model with integrated convolutional block attention mechanism","volume":"140","author":"Xu","year":"2023","journal-title":"Image and Vision Computing"},{"key":"10.1016\/j.ipm.2026.104788_bib0045","unstructured":"Xu, H., Liu, Y., Jiang, B., Peng, J., Luo, D., Hu, X., Yan, S., & Li, H. (2025). IRPO: Boosting image restoration via post-training GRPO. arXiv Preprint arXiv:2512.00814."},{"issue":"5","key":"10.1016\/j.ipm.2026.104788_bib0046","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1007\/s11280-017-0515-4","article-title":"CrimeTelescope: Crime hotspot prediction based on urban and social media data fusion","volume":"21","author":"Yang","year":"2018","journal-title":"World Wide Web"},{"key":"10.1016\/j.ipm.2026.104788_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.apgeog.2023.103025","article-title":"Investigating the effect of people on the street and streetscape physical environment on the location choice of street theft crime offenders using street view images and a discrete spatial choice model","volume":"157","author":"Yue","year":"2023","journal-title":"Applied Geography"},{"issue":"3","key":"10.1016\/j.ipm.2026.104788_bib0048","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1145\/3446776","article-title":"Understanding deep learning (still) requires rethinking generalization","volume":"64","author":"Zhang","year":"2021","journal-title":"Communications of the ACM"},{"key":"10.1016\/j.ipm.2026.104788_bib0049","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Zhang, R., Zhang, J., Ye, Y., Luo, Z., Feng, Z., & Ma, Y. (2024). Llamafactory: Unified efficient fine-tuning of 100+ language models. arXiv Preprint arXiv:2403.13372.","DOI":"10.18653\/v1\/2024.acl-demos.38"}],"container-title":["Information Processing &amp; Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001792?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001792?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T11:24:49Z","timestamp":1781954689000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326001792"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":49,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326001792"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104788","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Domain-Adapted Pipeline for Structured Information Extraction from Police Incident Announcements on Social Media","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104788","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104788"}}