{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T05:37:57Z","timestamp":1768973877835,"version":"3.49.0"},"reference-count":43,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2017,3,13]],"date-time":"2017-03-13T00:00:00Z","timestamp":1489363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2017,3,13]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to make the mobile e-commerce shopping more convenient and avoid information overload by a mobile e-commerce recommendation system using an improved Apriori algorithm.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Combined with the characteristics of the mobile e-commerce, an improved Apriori algorithm was proposed and applied to the recommendation system. This paper makes products that are recommended to consumers valuable by improving the data mining efficiency. Finally, a Taobao online dress shop is used as an example to prove the effectiveness of an improved Apriori algorithm in the mobile e-commerce recommendation system.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The results of the experimental study clearly show that the mobile e-commerce recommendation system based on an improved Apriori algorithm increases the efficiency of data mining to achieve the unity of real time and recommendation accuracy.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The improved Apriori algorithm is applied in the mobile e-commerce recommendation system solving the limitation of the visual interface in a mobile terminal and the mass data that are continuously generated. The proposed recommendation system provides greater prediction accuracy than conventional systems in data mining.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-03-2016-0094","type":"journal-article","created":{"date-parts":[[2017,3,6]],"date-time":"2017-03-06T03:53:21Z","timestamp":1488772401000},"page":"287-303","source":"Crossref","is-referenced-by-count":105,"title":["Application of an improved Apriori algorithm in a mobile e-commerce recommendation system"],"prefix":"10.1108","volume":"117","author":[{"given":"Yan","family":"Guo","sequence":"first","affiliation":[]},{"given":"Minxi","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020120901055085500_ref001","article-title":"Fast algorithms for mining association rules in large databases","year":"1994"},{"key":"key2020120901055085500_ref002","first-page":"207","article-title":"Mining association rules between sets 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