Online diet plan recommendation system presented in natural language

• Main Authors: Fabia, Gabriel Antonio G., Quebral, Marco Emil G., Yu, Miguelito T.
• Format: text
• Language: English
• Published: Animo Repository 2012
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/12094
• Institution: De La Salle University

Existing health recommender systems only present users with short descriptions and tables which would require users more effort in understanding the recommendation. Natural Language Generation (NLG) is a technology which involves converting computerized data into written text. A technology such as this can be beneficial to health recommender systems as it can provide users with a clearer understanding of the recommendation, but existing health recommender systems do not employ NLG. The system incorporates NLG into a health recommender system in order to generate a complete meal recommendation which consists of meal recipes, preparation process, and a meal recommendation explanation. Results of tests conducted by test users and field experts suggest that the system is well capable of presenting understandable and effective meal recommendations.