{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:24:01Z","timestamp":1767705841847,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant 61672261 and Grant 61802056"],"award-info":[{"award-number":["Grant 61672261 and Grant 61802056"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007847","name":"Natural Science Foundation of Jilin Province","doi-asserted-by":"publisher","award":["Grant 20180101043JC"],"award-info":[{"award-number":["Grant 20180101043JC"]}],"id":[{"id":"10.13039\/100007847","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Industrial Technology Research and Development Project of Jilin Development and Reform Commission","award":["Grant 2019C053-9"],"award-info":[{"award-number":["Grant 2019C053-9"]}]},{"name":"Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences","award":["Grant LSU-KFJJ-2019-08"],"award-info":[{"award-number":["Grant LSU-KFJJ-2019-08"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Market basket prediction, which is the basis of product recommendation systems, is the concept of predicting what customers will buy in the next shopping basket based on analysis of their historical shopping records. Although product recommendation systems develop rapidly and have good performance in practice, state-of-the-art algorithms still have plenty of room for improvement. In this paper, we propose a new algorithm combining pattern prediction and preference prediction. In pattern prediction, sequential rules, periodic patterns and association rules are mined and probability models are established based on their statistical characteristics, e.g., the distribution of periods of a periodic pattern, to make a more precise prediction. Products that have a higher probability will have priority to be recommended. If the quantity of recommended products is insufficient, then we make a preference prediction to select more products. Preference prediction is based on the frequency and tendency of products that appear in customers\u2019 individual shopping records, where tendency is a new concept to reflect the evolution of customers\u2019 shopping preferences. Experiments show that our algorithm outperforms those of the baseline methods and state-of-the-art methods on three of four real-world transaction sequence datasets.<\/jats:p>","DOI":"10.3390\/e23111430","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:21:08Z","timestamp":1635805268000},"page":"1430","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A New Method Combining Pattern Prediction and Preference Prediction for Next Basket Recommendation"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2319-4314","authenticated-orcid":false,"given":"Guisheng","family":"Chen","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"},{"name":"Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1648-8138","authenticated-orcid":false,"given":"Zhanshan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"},{"name":"Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1145\/170036.170072","article-title":"Mining association rules between sets of items in large databases","volume":"22","author":"Agrawal","year":"1993","journal-title":"ACM SIGMOD Rec."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"17233","DOI":"10.1007\/s00500-020-05015-2","article-title":"Deep learning-based sequential pattern mining for progressive database","volume":"24","author":"Jamshed","year":"2020","journal-title":"Soft Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2203","DOI":"10.1109\/TKDE.2015.2405509","article-title":"Mining partially-ordered sequential rules common to multiple sequences","volume":"27","author":"Wu","year":"2015","journal-title":"IEEE Trans. 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