Application Of A Hybrid Recommender System For Ethiopian Local Food Selection To Diabetes Type 2 Patients
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Date
2015-10-03
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Addis Ababa University
Abstract
Diabetes is becoming one of the rapidly increasing non-communicable diseases and an
important public health problem all over the world. Ethiopia is at a risk of increased
diabetes incidence. The number of deaths attributed to diabetes reached over 21,000 in
2007. Among this number, Type-2 diabetes constitutes about 85 to 95% of all diabetes.
Dietary management is considered to be one of the cornerstones of diabetes care. Good
diabetes management is a balance between healthy eating, exercise and medication.
The problem, however, is that most diabetic patients have difficulty of identifying the
recommended quality and quantity of food that they have to eat in order to control
their blood glucose.
The aim of the study is to assess the applicability of a hybrid filtering approach to create
a personalized food recommender system that can promote healthier eating habits. So
that, the patients can safely chooses a healthier food that can promote their self-dietary
management.
To achieve this goal, the study attempts to design and develop a prototype hybrid
recommender system which is a combination of both collaborative, content base and
demographic filtering methods with a mixed, cascade and switching hybrid strategies.
The knowledge is acquired using unstructured interviews from domain expert and relevant
documents analysis method is also applied to capture explicit knowledge. The data about
Ethiopian foods is collected from the food composition table from ENHRI booklet. The
prototype is developed by using SQL Server 2008 database with a visual Basic programming
language.
Moreover, in testing and evaluating the prototype system five volunteer patients were
involved. The experiment conducted in five iterations for each user. So the result shows
that, the recommender system has a good performance and achieved the desired goal.
But further research is needed to be conducted of exploring different options of hybrid
strategies.
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Hybrid Recommender System For Ethiopian Local Food Selection