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Idea is based on adaptive learning platform and function modules. We consider the individual differences between students, to students as the center, collect students\u2019 personalized learning demand data, and according to the data information to build student demand model. On the basis of using data mining methods for clustering recommendation service resources in learning, the adaptive recommend according to students\u2019 individual need is proposed. The experimental results show that the adaptive learning service recommendation algorithm based on big data has high recommendation accuracy, coverage rate and recall rate, which is of great significance in the actual learning service recommendation.<\/jats:p>","DOI":"10.1007\/s11036-021-01772-y","type":"journal-article","created":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T12:20:49Z","timestamp":1620044449000},"page":"2176-2187","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Improvement of Adaptive Learning Service Recommendation Algorithm Based on Big Data"],"prefix":"10.1007","volume":"26","author":[{"given":"Ya-zhi","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9073-5347","authenticated-orcid":false,"given":"Marcin","family":"Wo\u017aniak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,30]]},"reference":[{"issue":"7","key":"1772_CR1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.is.2018.01.006","volume":"79","author":"S Nadal","year":"2019","unstructured":"Nadal S, Romero O, Abell\u00f3 A (2019) An integration-oriented ontology to govern evolution in Big Data ecosystems. 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