{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T04:57:59Z","timestamp":1790657879003,"version":"4.1.0"},"reference-count":63,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Foods"],"abstract":"<jats:p>Food recommendation systems must satisfy dietary preferences and nutritional, health, and ingredient constraints. In constrained food knowledge-base question answering, unequal positive training-answer frequency may influence ranking without necessarily reflecting query\u2013recipe fit. We develop D-pFoodReQ by replacing the pFoodReQ answer ranker with BAMnet-D while retaining its food-knowledge and constraint-processing pipeline. BAMnet-D introduces a separate answer-frequency branch alongside semantic matching, applies candidate-set-relative loss reweighting, and uses a counterfactual-inspired intervention that sets the explicit frequency input to zero during validation and testing. Across three runs using the same protocol on the pFoodReQ benchmark, D-pFoodReQ achieved an F1 score of 62.96 \u00b1 2.06%, compared with 61.33 \u00b1 2.27% for pFoodReQ. Its mean average precision and mean average recall were 66.50 \u00b1 0.54% and 65.38 \u00b1 0.66%, respectively. On 1355 questions for which no gold answer appeared as a positive training label, D-pFoodReQ attained a mean answer-set F1 nearly identical to that of pFoodReQ while achieving higher Recall@5 and NDCG@5. Ablation and output-composition analyses indicated that loss reweighting alone did not account for the full improvement, while retaining the explicit frequency term was associated with a larger share of answers observed as positive training labels. These results support answer-frequency-aware ranking for constrained food knowledge-base question answering.<\/jats:p>","DOI":"10.3390\/foods15193418","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T16:29:53Z","timestamp":1790267393000},"page":"3418","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["D-pFoodReQ: Answer-Frequency-Aware Debiasing for Constrained Knowledge-Base Question Answering in Food Recommendation"],"prefix":"10.3390","volume":"15","author":[{"given":"Zhifang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai 264025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenchao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai 264025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6790-0239","authenticated-orcid":false,"given":"Guorui","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai 264025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yancun","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai 264025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6668-9208","authenticated-orcid":false,"given":"Weiqing","family":"Min","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuqiang","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"ref_1","first-page":"92:1","article-title":"A Survey on Food Computing","volume":"52","author":"Min","year":"2019","journal-title":"ACM Comput. 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