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  • 标题:Automated Menu Recommendation System Based on Past Preferences
  • 本地全文:下载
  • 作者:Daniel Simon Sanz ; Ankur Agrawal
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2014
  • 卷号:5
  • 期号:7
  • DOI:10.14569/IJACSA.2014.050711
  • 出版社:Science and Information Society (SAI)
  • 摘要:Data mining plays an important role in ecommerce in today’s world. Time is critical when it comes to shopping as options are unlimited and making a choice can be tedious. This study presents an application of data mining in the form of an Android application that can provide user with automated suggestion based on past preferences. The application helps a person to choose what food they might want to order in a specific restaurant. The application learns user behavior with each order - what they order in each kind of meal and what are the products that they select together. After gathering enough information, the application can suggest the user about the most selected dish in the recent past and since the application started to learn. Applications, such as these, can play a major role in helping make a decision based on past preferences, thereby reducing the user involvement in decision making.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; data mining; Apriori; Android; restaurant; recommendation system
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