Information Extraction from Unstructured Data Sets: An Application to Cardiac Arrhythmia Detection

Autor:	Omar Behadada
Rok vydání:	2015
Předmět:	business.industry Computer science Experimental data Cardiac arrhythmia Unstructured data computer.software_genre Fuzzy logic Field (computer science) Information extraction Text mining Knowledge extraction Data analysis Data mining business computer
Zdroj:	Big-Data Analytics and Cloud Computing ISBN: 9783319253114 Big-Data Analytics and Cloud Computing
DOI:	10.1007/978-3-319-25313-8_9
Popis:	In this chapter, we will discuss a case study, which semi-automatically defines fuzzy partition rules to provide a powerful and accurate insight into cardiac arrhythmia. In particular, this is based on large unstructured data sets in the form of scientific papers focusing on cardiology. The information extracted is subsequently combined with expert knowledge, as well as experimental data, to provide a robust, scalable and accurate system. The evaluation clearly shows a high accuracy rate, namely, 92.6 %, as well as transparency of the system, which is a remarkable improvement with respect to the current research in the field.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7bf0fd2d8513f04ec0d8bf5da6cc85c0 https://doi.org/10.1007/978-3-319-25313-8_9 Zobrazit plný text záznamu