Title: An architectural framework for knowledge extraction from meteorological data

Authors: Sagar S. De; Minati Mishra; Satchidananda Dehuri

Addresses: Computer Services Cell, S.N. Bose National Centre for Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata-700 098, India ' Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore-756 019, Odisha, India ' Department of Systems Engineering, Ajou University, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Korea

Abstract: The methods of knowledge extraction from spatio-temporal data such as meteorological domain suffer from various problems like missing values, noise, improper format, and large in volume. Therefore, data pre-processing and reorganisation are the important concerns of this domain. In this paper, we have discussed a layered framework for data fetching, pre-processing and persisting. Further, we develop knowledge extraction modules for supporting the future extensibility and reusing well established tools. We have presented experimental results achieved using this architecture, in addition to its other potential benefits.

Keywords: knowledge extraction; meteorology data; automated data warehousing; meteorological data warehouse; data pre-processing; summary-based knowledge mining.

DOI: 10.1504/IJAMS.2014.067195

International Journal of Applied Management Science, 2014 Vol.6 No.4, pp.323 - 342

Published online: 07 Feb 2015 *

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