User's Profile Ontology-based Semantic Framework for Personalized Food and Nutrition Recommendation

摘要

People depend on popular search engines, like Google and Yahoo, to retrieve the desired information from the Web. Searching for the right food, to eat, is an example of the frequent queries on the Web where people do not find relevant information easily. One reason for this un-satisfaction is the fact that many people have personal preferences where each one likes and dislikes certain food. Also, some people have specific health conditions that restrict their food choices and encourage them to take other food. In addition, the cultures, where people live in, influence food choices and varieties. Therefore, it will be helpful to develop a framework that provides food recommendation, what to take and what to avoid, increasing the advantages and reducing the risks especially for people who have long term diseases such as diabetes and high-blood-pressure. Since health and nutrition information is critical and hence people need to get precise information from trusted sources. Furthermore, transforming the implied knowledge about health and nutrition into structured data is challenging, so developing a framework that semantically manipulate the health and nutrition information is becoming an increasingly important research topic. In this paper, we harness semantic Web and ontology engineering technologies to analyze user's preferences, construct a nutritional and health oriented user's profile, and use the profile to organize the related knowledge so that users can make smarter food and health inquires. We present a semantic framework that uses the personalization techniques based on integrated domain ontologies, pre-constructed by domain experts, to recommend the relevant food that is consistent with people's needs. The empirical evaluation of the proposed framework shows promising results for recommending the relevant food information with a superior user's satisfaction.