{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T14:19:13Z","timestamp":1769955553212,"version":"3.49.0"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004070","name":"Khalifa University","doi-asserted-by":"publisher","award":["RIG-2023-049"],"award-info":[{"award-number":["RIG-2023-049"]}],"id":[{"id":"10.13039\/501100004070","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.eswa.2025.129851","type":"journal-article","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T03:58:57Z","timestamp":1758772737000},"page":"129851","update-policy":"https:\/\/linproxy.fan.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PC","title":["LLM-based exploration and analysis of real-time and historical blockchain data"],"prefix":"10.1016","volume":"298","author":[{"given":"S.","family":"Gebreab","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0001-5153-2558","authenticated-orcid":false,"given":"A.","family":"Musamih","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-2310-2558","authenticated-orcid":false,"given":"K.","family":"Salah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-2749-2688","authenticated-orcid":false,"given":"R.","family":"Jayaraman","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"9","key":"10.1016\/j.eswa.2025.129851_bib0001","doi-asserted-by":"crossref","first-page":"5047","DOI":"10.1007\/s10115-024-02120-8","article-title":"An analysis of large language models: Their impact and potential applications","volume":"66","author":"Bharathi Mohan","year":"2024","journal-title":"Knowledge and Information Systems"},{"key":"10.1016\/j.eswa.2025.129851_bib0002","doi-asserted-by":"crossref","unstructured":"Bouchiha, M. A., Telnoff, Q., Bakkali, S., Champagnat, R., Rabah, M., Coustaty, M., & Ghamri-Doudane, Y. (2024). LLMChain: Blockchain-based reputation system for sharing and evaluating large language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2404.13236.","DOI":"10.1109\/COMPSAC61105.2024.00067"},{"key":"10.1016\/j.eswa.2025.129851_bib0003","unstructured":"Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., & Amodei, D. (2020). Language models are few-shot learners. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2005.14165."},{"key":"10.1016\/j.eswa.2025.129851_bib0004","unstructured":"Buterin, V. (2014). A next-generation smart contract and decentralized application platform. White paper. https:\/\/linproxy.fan.workers.dev:443\/https\/ethereum.org\/en\/whitepaper\/."},{"key":"10.1016\/j.eswa.2025.129851_bib0005","unstructured":"ChainGPT (2025). AIVM (artificial intelligence virtual machine) whitepaper: The layer-1 infrastructure for a transparent, scalable ai economy. Accessed: 2025-06-23 https:\/\/linproxy.fan.workers.dev:443\/https\/tinyurl.com\/2pn4t6a7."},{"issue":"240","key":"10.1016\/j.eswa.2025.129851_bib0006","first-page":"1","article-title":"PaLM: Scaling language modeling with pathways","volume":"24","author":"Chowdhery","year":"2023","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.eswa.2025.129851_bib0007","doi-asserted-by":"crossref","unstructured":"Douze, M., Guzhva, A., Deng, C., Johnson, J., Szilvasy, G., Mazar\u00e9, P.-E., Lomeli, M., Hosseini, L., & J\u00e9gou, H. (2025). The Faiss library. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2401.08281.","DOI":"10.1109\/TBDATA.2025.3618474"},{"key":"10.1016\/j.eswa.2025.129851_bib0008","unstructured":"Gai, Y., Zhou, L., Qin, K., Song, D., & Gervais, A. (2023). Blockchain large language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2304.12749."},{"issue":"1","key":"10.1016\/j.eswa.2025.129851_bib0009","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pdig.0000417","article-title":"Peer review of GPT-4 technical report and systems card","volume":"3","author":"Gallifant","year":"2024","journal-title":"PLOS Digital Health"},{"key":"10.1016\/j.eswa.2025.129851_bib0010","unstructured":"Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval-augmented generation for large language models: A survey. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2312.10997."},{"key":"10.1016\/j.eswa.2025.129851_bib0011","series-title":"2024 12th International symposium on digital forensics and security (ISDFS)","first-page":"1","article-title":"LLM-based framework for administrative task automation in healthcare","author":"Gebreab","year":"2024"},{"key":"10.1016\/j.eswa.2025.129851_bib0028","unstructured":"Gemini Team, Google (2024). Gemini: A family of highly capable multimodal models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2312.11805."},{"key":"10.1016\/j.eswa.2025.129851_bib0012","unstructured":"Geren, C., Board, A., Dagher, G. G., Andersen, T., & Zhuang, J. (2024). Blockchain for large language model security and safety: A holistic survey. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2407.20181."},{"key":"10.1016\/j.eswa.2025.129851_bib0013","unstructured":"Guu, K., Lee, K., Tung, Z., Pasupat, P., & Chang, M.-W. (2020). REALM: Retrieval-augmented language model pre-training. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2002.08909."},{"key":"10.1016\/j.eswa.2025.129851_bib0014","unstructured":"He, Z., Li, Z., Yang, S., Ye, H., Qiao, A., Zhang, X., Luo, X., & Chen, T. (2025). Large language models for blockchain security: A systematic literature review. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2403.14280."},{"key":"10.1016\/j.eswa.2025.129851_bib0015","doi-asserted-by":"crossref","unstructured":"Izacard, G., & Grave, E. (2021). Leveraging passage retrieval with generative models for open domain question answering. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2007.01282.","DOI":"10.18653\/v1\/2021.eacl-main.74"},{"key":"10.1016\/j.eswa.2025.129851_bib0016","unstructured":"Jacob, M., Lindgren, E., Zaharia, M., Carbin, M., Khattab, O., & Drozdov, A. (2024). Drowning in documents: Consequences of scaling reranker inference. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2411.11767."},{"key":"10.1016\/j.eswa.2025.129851_bib0017","article-title":"Learning postgreSQL","author":"Juba","year":"2015"},{"key":"10.1016\/j.eswa.2025.129851_bib0018","doi-asserted-by":"crossref","unstructured":"Kamalloo, E., Zhang, X., Ogundepo, O., Thakur, N., Alfonso-Hermelo, D., Rezagholizadeh, M., & Lin, J. (2023). Evaluating embedding APIs for information retrieval. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2305.06300.","DOI":"10.18653\/v1\/2023.acl-industry.50"},{"key":"10.1016\/j.eswa.2025.129851_bib0019","unstructured":"Kim, H., Jeon, T., Choi, S., Choi, S., & Cho, H. (2024). FLEX: Expert-level false-less execution metric for reliable text-to-SQL benchmark. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2409.19014."},{"key":"10.1016\/j.eswa.2025.129851_bib0020","unstructured":"Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., K\u00fcttler, H., Lewis, M., Yih, W.-t., Rockt\u00e4schel, T., Riedel, S., & Kiela, D. (2021). Retrieval-augmented generation for knowledge-intensive NLP tasks. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2005.11401."},{"key":"10.1016\/j.eswa.2025.129851_bib0021","doi-asserted-by":"crossref","unstructured":"Luo, H., Luo, J., & Vasilakos, A. V. (2023). BC4LLM: Trusted artificial intelligence when blockchain meets large language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2310.06278.","DOI":"10.1016\/j.neucom.2024.128089"},{"key":"10.1016\/j.eswa.2025.129851_bib0022","series-title":"ECIS 2022 research papers","article-title":"Decentralized finance \u2013 A systematic literature review and research directions","author":"Meyer","year":"2022"},{"key":"10.1016\/j.eswa.2025.129851_bib0023","doi-asserted-by":"crossref","first-page":"117134","DOI":"10.1109\/ACCESS.2019.2936094","article-title":"A survey of blockchain from the perspectives of applications, challenges, and opportunities","volume":"7","author":"Monrat","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2025.129851_bib0024","unstructured":"Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. White paper. https:\/\/linproxy.fan.workers.dev:443\/https\/bitcoin.org\/bitcoin.pdf."},{"key":"10.1016\/j.eswa.2025.129851_bib0025","unstructured":"Pourreza, M., Li, H., Sun, R., Chung, Y., Talaei, S., Kakkar, G. T., Gan, Y., Saberi, A., Ozcan, F., & Arik, S. O. (2024). CHASE-SQL: Multi-path reasoning and preference optimized candidate selection in Text-to-SQL. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2410.01943."},{"key":"10.1016\/j.eswa.2025.129851_bib0026","unstructured":"Shi, L., Tang, Z., Zhang, N., Zhang, X., & Yang, Z. (2024). A survey on employing large language models for text-to-SQL tasks. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2407.15186."},{"key":"10.1016\/j.eswa.2025.129851_bib0027","unstructured":"Talaei, S., Pourreza, M., Chang, Y.-C., Mirhoseini, A., & Saberi, A. (2024). CHESS: Contextual harnessing for efficient SQL synthesis. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2405.16755."},{"key":"10.1016\/j.eswa.2025.129851_bib0029","unstructured":"Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozi\u00e8re, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., & Lample, G. (2023). Llama: Open and efficient foundation language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2302.13971."},{"issue":"7","key":"10.1016\/j.eswa.2025.129851_bib0030","doi-asserted-by":"crossref","first-page":"3135","DOI":"10.1109\/TVCG.2019.2963018","article-title":"Visualization of blockchain data: A systematic review","volume":"27","author":"Tovanich","year":"2021","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"10.1016\/j.eswa.2025.129851_bib0031","unstructured":"Toyoda, K., Wang, X., Li, M., Gao, B., Wang, Y., & Wei, Q. (2024). Blockchain data analysis in the era of large-language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2412.09640."},{"issue":"6","key":"10.1016\/j.eswa.2025.129851_bib0032","doi-asserted-by":"crossref","DOI":"10.1007\/s11704-024-40231-1","article-title":"A survey on large language model based autonomous agents","volume":"18","author":"Wang","year":"2024","journal-title":"Frontiers of Computer Science"},{"key":"10.1016\/j.eswa.2025.129851_bib0033","series-title":"Proceedings of the 36th International Conference on Neural Information Processing Systems (NeurIPS)","first-page":"1800","article-title":"Chain-of-thought prompting elicits reasoning in large language models","author":"Wei","year":"2022"},{"key":"10.1016\/j.eswa.2025.129851_bib0034","first-page":"30","article-title":"SoK: Decentralized finance (DeFi)","author":"Werner","year":"2023"},{"key":"10.1016\/j.eswa.2025.129851_bib0035","article-title":"Ethereum: A secure decentralised generalised transaction ledger","author":"Wood","year":"2014","journal-title":"Ethereum Project Yellow Paper"},{"key":"10.1016\/j.eswa.2025.129851_bib0036","unstructured":"Xian, Y., Zeng, X., Xuan, D., Yang, D., Li, C., Fan, P., & Liu, P. (2024). Connecting large language models with blockchain: Advancing the evolution of smart contracts from automation to intelligence. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2412.02263."},{"issue":"1","key":"10.1016\/j.eswa.2025.129851_bib0037","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s40854-019-0147-z","article-title":"A systematic review of blockchain","volume":"5","author":"Xu","year":"2019","journal-title":"Financial Innovation"},{"key":"10.1016\/j.eswa.2025.129851_bib0038","unstructured":"Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, C., Chen, Y., Chen, Z., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., Liu, P., Nie, J. Y., & Wen, J. R. (2025). A survey of large language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2303.18223."},{"key":"10.1016\/j.eswa.2025.129851_bib0039","unstructured":"Zhong, V., Xiong, C., & Socher, R. (2017). Seq2SQL: GGenerating structured queries from natural language using reinforcement learning. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/1709.00103."},{"key":"10.1016\/j.eswa.2025.129851_bib0040","unstructured":"Zhu, Y., Li, J., Li, G., Zhao, Y., Li, J., Jin, Z., & Mei, H. (2023). Hot or cold? Adaptive temperature sampling for code generation with large language models. https:\/\/linproxy.fan.workers.dev:443\/https\/arxiv.org\/abs\/2309.02772."}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0957417425034669?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0957417425034669?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T23:29:16Z","timestamp":1769902156000},"score":1,"resource":{"primary":{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417425034669"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":40,"alternative-id":["S0957417425034669"],"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/doi.org\/10.1016\/j.eswa.2025.129851","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"LLM-based exploration and analysis of real-time and historical blockchain data","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/linproxy.fan.workers.dev:443\/https\/doi.org\/10.1016\/j.eswa.2025.129851","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"129851"}}