基于模糊逻辑的自适应食物建议引擎

Tousif Osman, Maisha Mahjabeen, Shahreen Shahjahan Psyche, A. Urmi, J. M. S. Ferdous, R. Rahman
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引用次数: 4

摘要

本研究提出了一种根据用户偏好对食物列表进行搜索和排序的方法。该系统维护一个模糊数据库来存储餐馆及其菜单,并为每个项目提供一些特定的参数。系统允许用户指定他们感兴趣的食物口味,他们喜欢吃的地点名称,每个人的大致预算和其他一些定义参数作为搜索关键字。在搜索时,系统根据用户自定义参数从数据库中获取条目,将每个条目的元数据转换为模糊参数,并将列表传递给模糊控制器。然后控制器分配一个分数作为每个项目的输出。最后,按降序对列表进行排序。系统允许用户提供关于食物的反馈,使系统具有适应性。系统还可以根据每个用户的口味进行缩放,因为每个用户的食物口味差异很大;因此,该系统提供了更精确的结果,使其成为一个完整的食品搜索引擎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive food suggestion engine by fuzzy logic
The research proposes an approach for searching and sorting food list according to user preference. The system maintains a fuzzy database to store restaurants and their menus with some specific parameters for each item. System allows the user to specify food tastes that are of their interest, location name where they prefer to eat, approximated budget for each person and few other defined parameters as searching keyword. While searching, the system will fetch the entries from the database according to user defined parameters, convert each item's metadata to fuzzy parameters and pass the list to a fuzzy controller. Then the controller assigns a score as an output to each item. Finally the list is sorted in descending order. System allows the users to provide the feedback about the food which makes the system to be adaptive. System also gets scaled for each individual user as food taste varies significantly for individual users; hence the system provides more precise result and makes it a complete food searching engine.
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