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Knowledge discovery in unstructured, big data


Abu Muntalib, Shamsiah and Sidi, Fatimah and A. Jabar, Marzanah and Ishak, Iskandar (2014) Knowledge discovery in unstructured, big data. In: Malaysian National Conference of Databases 2014 (MaNCoD 2014), 17 Sept. 2014, Universiti Putra Malaysia, Serdang, Selangor. (pp. 50-54).


Knowledge may be discovered from various sources of information. Knowledge Discovery in Database (KDD) is the process of discovering valuable knowledge from data collection. Data warehousing, traditional data processing and analysis of structured data through the Relationship Database Management System (RDBMS) is access to a standard IT technology. However, RDBMS cannot satisfy the challenges of Big Data. The current biggest challenge is a matter of turning Big Data into Knowledge Discovery insight that enable organizations to facilitate effective decision making. The purpose of this paper is to explore techniques in knowledge discovery and the challenges in Big Data real-time setting. A technique of knowledge discovery in real-time insight will be proposed in order to extract valuable knowledge.

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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
Keywords: Knowledge discovery; Real-time; Big data
Depositing User: Nursyafinaz Mohd Noh
Date Deposited: 07 Jul 2015 08:58
Last Modified: 23 Oct 2018 01:48
URI: http://psasir.upm.edu.my/id/eprint/39244
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