Title :
FML-Based Recommender System for Restaurants
Author :
Woan-Tyng Lin ; Mei-Hui Wang ; Chang-Shing Lee ; Kurozumi, Kanta ; Majima, Yukie
Author_Institution :
Nat. Univ. of Tainan, Tainan, Taiwan
Abstract :
Due to the increasing number of obese people, this paper presents a Fuzzy Markup Language (FML)-based recommender system for restaurants to infer the recommended level of a restaurant by giving the estimated calories in food, the distance to the restaurant, and the price of the served food. With the standard of the Food Exchange List (FEL), developed by The Japan Diabetes Society, and the information about the food calories, we can estimate the calories of different kinds of the food. We first construct the ontology of this system, and then we use the FML to build the knowledge base and the rule base of the recommender system based on domain experts´ suggestions and Japanese persons´ experience in diet. With the input of the estimated calories of food, distance of the restaurant, and price of the food, the recommended level of the restaurant is inferred to allow people to both enjoy the delicious food and make an exercise.
Keywords :
XML; catering industry; food safety; knowledge based systems; ontologies (artificial intelligence); recommender systems; FEL; FML-based recommender system; Food Exchange List; Japanese person experience; The Japan Diabetes Society; delicious food; domain expert suggestions; food calorie estimation; fuzzy markup language-based recommender system; ontology; restaurants; Diabetes; Educational institutions; Fuzzy logic; Knowledge based systems; Ontologies; Recommender systems; Simulation; Food Exchange List; Fuzzy Markup Language; Ontology; Recommender System;
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2013 Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4799-2528-5
DOI :
10.1109/TAAI.2013.54
