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

Print

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.

This document is currently not available here.

Share

COinS