Context Inference and Sensor Data Classification of Big Data Stream Environment
نویسندگان
چکیده
منابع مشابه
Big Data Quality: From Content to Context
Over the last 20 years, and particularly with the advent of Big Data and analytics, the research area around Data and Information Quality (DIQ) is still a fast growing research area. There are many views and streams in DIQ research, generally aiming at improving the effectiveness of decision making in organizations. Although there are a lot of researches aimed at clarifying the role of BIG data...
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با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
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15 صفحه اولDetecting Concept Drift in Data Stream Using Semi-Supervised Classification
Data stream is a sequence of data generated from various information sources at a high speed and high volume. Classifying data streams faces the three challenges of unlimited length, online processing, and concept drift. In related research, to meet the challenge of unlimited stream length, commonly the stream is divided into fixed size windows or gradual forgetting is used. Concept drift refer...
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Big data time series data streams are ubiquitous in finance, meteorology and engineering. It may be impossible to process an entire “big data” continuous data stream or to scan through it multiple times due to its tremendous volume. In Heraclitus’s well-known saying, “you never step in the same stream twice,” and so it is with “big data” temporal data streams. Unlike traditional data sets, big ...
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ژورنال
عنوان ژورنال: The Journal of the Korea institute of electronic communication sciences
سال: 2014
ISSN: 1975-8170
DOI: 10.13067/jkiecs.2014.9.10.1079