Online diet plan recommendation system presented in natural language
Date of Publication
2012
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Nathalie Rose Lim-Cheng
Defense Panel Member
Gian Kristian A. Fontanilla
Kelvin C. Chua
Abstract/Summary
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.
Abstract Format
html
Language
English
Format
Accession Number
TU18551
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1 v. (various foliations) ; 28 cm. + ; 1 computer optical disc.
Recommended Citation
Fabia, G. G., Quebral, M. G., & Yu, M. T. (2012). Online diet plan recommendation system presented in natural language. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/12094