RECOMMENDER SYSTEM FOR PERSONALISED WELLNESS THERAPY
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 9
Abstract
Rising costs and risks in health care have shifted the preference of individuals from health treatment to disease prevention. This prevention treatment is known as wellness. In recent years, the Internet has become a popular place for wellness-conscious users to search for wellness-related information and solutions. As the user community becomes more wellness conscious, service improvement is needed to help users find relevant personalised wellness solutions. Due to rapid development in the wellness market, users value convenient access to wellness services. Most wellness websites reflect common health informatics approaches; these amount to more than 70,000 sites worldwide. Thus, the wellness industry should improve its Internet services in order to provide better and more convenient customer service. This paper discusses the development of a wellness recommender system that would help users find and adapt suitable personalised wellness therapy treatments based on their individual needs. This paper introduces new approaches that enhance the convenience and quality of wellness information delivery on the Internet. The wellness recommendation task is performed using an Artificial Intelligence technique of hybrid case-based reasoning (HCBR). HCBR solves users’ current wellness problems by applying solutions from similar cases in the past. From the evaluation results for our prototype wellness recommendation system, we conclude that wellness consultants are using consistent wellness knowledge to recommend solutions for sample wellness cases generated through an online consultation form. Thus, the proposed model can be integrated into wellness websites to enable users to search for suitable personalized wellness therapy treatment based on their health condition.
Authors and Affiliations
Thean Lim, Wahidah Husain, Nasriah Zakaria
SentiTFIDF – Sentiment Classification using Relative Term Frequency Inverse Document Frequency
Sentiment Classification refers to the computational techniques for classifying whether the sentiments of text are positive or negative. Statistical Techniques based on Term Presence and Term Frequency, using Support Vec...
Using Induced Fuzzy Bi-Model to Analyze Employee Employer Relationship in an Industry
The employee-employer relationship is an intricate one. In an industry, the employers expect to achieve performances in quality and production in order to earn profit, on the other side employees need good pay and all po...
A Novel Security Scheme based on Twofish and Discrete Wavelet Transform
Nowadays, there is a huge amount of data exchanged between different users; the security of the exchanged data has become a significant problem due to the existing of several security attacks. So, to increase the confide...
Choosing a Career Based Personality Matching: A Case Study of King Abdulaziz University
Traditionally, selecting a career involves matching the specific aptitudes and characteristics of an individual with a career which requires or involves such factors. This particular approach has as its foundation the fa...
Robust Face Detection Using Circular Multi Block Local Binary Pattern and Integral Haar Features
In real world applications, it is very challenging to implement a good detector which gives best performance with great speed and accuracy. There is always a trade-off in terms of speed and accuracy, when we consider per...