Abstract: In this paper the authors present the framework of a
system for assisting users through counseling on personal health, the
Personal Health Assistance Service Expert System (PHASES).
Personal health assistance systems need Personal Health Records
(PHR), which support wellness activities, improve the understanding
of personal health issues, enable access to data from providers of
health services, strengthen health promotion, and in the end improve
the health of the population. This is especially important in societies
where the health costs increase at a higher rate than the overall
economy. The most important elements of a healthy lifestyle are
related to food (such as balanced nutrition and diets), activities for
body fitness (such as walking, sports, fitness programs), and other
medical treatments (such as massage, prescriptions of drugs). The
PHASES framework uses an ontology of food, which includes
nutritional facts, an expert system keeping track of personal health
data that are matched with medical treatments, and a comprehensive
data transfer between patients and the system.
Abstract: Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.