{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:10:16Z","timestamp":1780355416573,"version":"3.54.1"},"reference-count":45,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Key Scientific Research Project of Higher Education Institutions in Henan Province","award":["24A520060"],"award-info":[{"award-number":["24A520060"]}]},{"name":"the Key Scientific Research Project of Higher Education Institutions in Henan Province","award":["JG202434"],"award-info":[{"award-number":["JG202434"]}]},{"name":"the Key Scientific Research Project of Higher Education Institutions in Henan Province","award":["2025054"],"award-info":[{"award-number":["2025054"]}]},{"name":"Graduate Education and Teaching Reform Research Project of Zhongyuan University of Technology","award":["24A520060"],"award-info":[{"award-number":["24A520060"]}]},{"name":"Graduate Education and Teaching Reform Research Project of Zhongyuan University of Technology","award":["JG202434"],"award-info":[{"award-number":["JG202434"]}]},{"name":"Graduate Education and Teaching Reform Research Project of Zhongyuan University of Technology","award":["2025054"],"award-info":[{"award-number":["2025054"]}]},{"name":"Guidance Project of the China National Textile and Apparel Council","award":["24A520060"],"award-info":[{"award-number":["24A520060"]}]},{"name":"Guidance Project of the China National Textile and Apparel Council","award":["JG202434"],"award-info":[{"award-number":["JG202434"]}]},{"name":"Guidance Project of the China National Textile and Apparel Council","award":["2025054"],"award-info":[{"award-number":["2025054"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Query reformulation techniques optimize user queries to better align with documents, thus improving the performance of Information Retrieval (IR) systems. Previous methods have primarily focused on query expansion using techniques such as synonym replacement to improve recall. With the rapid advancement of Large Language Models (LLMs), the knowledge embedded within these models has grown. Research in prompt engineering has introduced various methods, with prompt chaining proving particularly effective for complex tasks. Directly prompting LLMs to reformulate queries has become a viable approach. However, existing LLM-based prompt methods for query reformulation often introduce irrelevant content into reformulated queries, resulting in decreased retrieval precision and misalignment with user intent. We propose a novel approach called Hierarchical Prompt Chaining for Query Reformulation (HiPC-QR). HiPC-QR employs a two-step prompt chaining technique to extract keywords from the original query and refine its structure by filtering out non-essential keywords based on the user\u2019s query intent. This process reduces the query\u2019s restrictiveness while simultaneously expanding essential keywords to enhance retrieval effectiveness. We evaluated the effectiveness of HiPC-QR on two benchmark retrieval datasets, namely MS MARCO and TREC Deep Learning.The experimental results show that HiPC-QR outperforms existing query reformulation methods on large-scale datasets in terms of both recall@10 and MRR@10.<\/jats:p>","DOI":"10.3390\/info16090790","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T10:50:04Z","timestamp":1757587804000},"page":"790","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["HiPC-QR: Hierarchical Prompt Chaining for Query Reformulation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6720-4831","authenticated-orcid":false,"given":"Hua","family":"Yang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Zhongyuan University of Technology, Zhengzhou 450007, China"},{"name":"VISTA Lab, Algoritmi Center, University of \u00c9vora, 7000-671 \u00c9vora, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanyang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Zhongyuan University of Technology, Zhengzhou 450007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1323-0249","authenticated-orcid":false,"given":"Teresa","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"VISTA Lab, Algoritmi Center, University of \u00c9vora, 7000-671 \u00c9vora, Portugal"},{"name":"Department of Computer Science, University of \u00c9vora, 7000-671 \u00c9vora, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1108\/eb026866","article-title":"On term selection for query expansion","volume":"46","author":"Robertson","year":"1990","journal-title":"J. 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