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دسته بندی:
داده کاوی - data mining
سال انتشار:
2018
عنوان انگلیسی مقاله:
Mining productive-periodic frequent patterns in tele-health systems
ترجمه فارسی عنوان مقاله:
کاوش الگوهای تکراری دوره ای تولیدی در سیستم های بهداشت و درمان
منبع:
Sciencedirect - Elsevier - Journal of Network and Computer Applications, 115 (2018) 33-47: doi:10:1016/j:jnca:2018:04:014
نویسنده:
Walaa N. Ismaila, Mohammad Mehedi Hassana,∗, Hessah A. Alsalamaha, Giancarlo Fortinob
چکیده انگلیسی:
Recently, tele-health systems have gained attention from vast research fields because they facilitate remote
monitoring of patients (e.g. vital sign data, physical activities, etc.) by utlizing various technologies such as body
sensor network, wireless communications, multimedia and human-computer interactions without interrupting
the quality of lifestyle. As tele-health generates a huge amount of healthcare data consisting of much useful
information, finding hidden information from the data is an important task. The purpose of this work is to
facilitate a real-time warning alarm in the context of tele-health remote monitoring using data mining techni
ques. This can be utilized for the e-wellbeing applications, for example, rehabilitation, early identification of
therapeutic issues and emergency warning. In particular, we focus on mining Productive Periodic frequent
patterns from incremental databases (such as vital sign data of patients) for various decision makings. Exploring
the correlations between periodic frequent vital sign data or items is important since the inherent relationships
between the items of patterns are relevant. To mine the correlated periodic frequent patterns from incremental
databases, we introduce the productive (i.e. useful) periodic frequent patterns (PPFP) as the set of periodic
frequent patterns with periodicities that result from the occurrence of correlated items. We finally design and
develop an efficient PPFP mining technique that can mine the complete set of useful periodically occurring
patterns in incremental databases. Numerous experiments were performed on both real and synthetic data set to
judge the effectiveness of the proposed pattern mining procedure when contrasted with existing best in class
approaches.
Keywords: Tele-health ، Data mining ، Productive periodic frequent patterns ، Periodic patterns ، Incremental database ، Fp-growth
قیمت: رایگان
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