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Published in Chapter:
Industrial Informatics: Assertion of Knowledge from Raw Industrial Data
Iram Shahzadi (Al-Khawarizmi Institute of Computer Science, University of Engineering & Technology, Pakistan), Qanita Ahmad (Al-Khawarizmi Institute of Computer Science, University of Engineering & Technology, Pakistan), and Imran Sarwar (Al-Khawarizmi Institute of Computer Science, University of Engineering & Technology, Pakistan)
Copyright: © 2012
|Pages: 25
DOI: 10.4018/978-1-4666-0294-6.ch010
Abstract
Correct and timely access to business information is the key to success in industry. However in industry, data is generated on daily basis and increases exponentially. Therefore, managing it is a challenging task for every organization. To deal with this phenomenon of information overload, organizations are in dire need to find and set up potential means for the analysis of raw industrial data (i.e. texts) and draw necessary information from it. This information can result in knowledge and knowledge leads towards wisdom, the essence of every business. This chapter is concerned with the use of knowledge management systems to cater information overload hassles, the organizations are facing today. As a solution, a detailed study of currently existing open source data and knowledge management systems is conducted. Hence, this chapter discusses the state of the art tools and technologies in this domain, and highlights the need and importance of semantic applications for industrial data processing.