2017Unpublished venueRequires access

Research on, and Development of, Data Extraction and Data Cleaning Technology Based on the Internet of Things

Zhaochan Li, Lili Sun, Russell Higgs

Open publisher page 3 citations

Abstract

This paper introduces the technological techniques of data cleaning and data extraction. The current state of domestic and international research in these two areas is reviewed and their future development considered. The following concepts are all explained: the basic principle of data cleaning, the framework models, the need for and the objectives of data cleaning, the testing method and the cleaning tool. Also introduced are data extraction techniques such as static data capture, log file capture, database generator capture, date and time capture, file comparison capture and finally source application capture. Finally the advantages and disadvantages of these various data extraction technologies and which to use in real-life situations are considered.

About this research paper

What this paper is about

This paper introduces the technological techniques of data cleaning and data extraction. The current state of domestic and international research in these two areas is reviewed and their future development considered. The following concepts are all explained: the basic principle of data cleaning, the framework models, the need for and the objectives of data cleaning, the testing method and the cleaning tool. Also introduced are data extraction techniques such as static data capture, log file capture, database generator capture, date and time capture, file comparison capture and finally source application capture. Finally the advantages and disadvantages of these various data extraction technologies and which to use in real-life situations are considered.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

This paper introduces the technological techniques of data cleaning and data extraction. The current state of domestic and international research in these two areas is reviewed and their future development considered. The following concepts are all explained: the basic principle of data cleaning, the framework models, the need for and the objectives of data cleaning, the testing method and the cleaning tool. Also introduced are data extraction techniques such as static data capture, log file capture, database generator capture, date and time capture, file comparison capture and finally source application capture. Finally the advantages and disadvantages of these various data extraction technologies and which to use in real-life situations are considered.

Key concepts: Data extraction, Computer science, Automatic identification and data capture, Generator (circuit theory), Database, The Internet, Extraction (chemistry), Data mining

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