IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Knowledge-Based Decision Support System for Analyzing the Relevancies of Various Attributes Based on Their Characteristics

Knowledge-Based Decision Support System for Analyzing the Relevancies of Various Attributes Based on Their Characteristics
View Sample PDF
Author(s): C. Madana Kumar Reddy (Annamacharya Institute of Technology and Sciences, India)
Copyright: 2017
Pages: 10
Source title: Web Data Mining and the Development of Knowledge-Based Decision Support Systems
Source Author(s)/Editor(s): G. Sreedhar (Rashtriya Sanskrit Vidyapeetha (Deemed University), India)
DOI: 10.4018/978-1-5225-1877-8.ch011

Purchase


Abstract

Data mining extracts novel and useful knowledge from large repositories of data and has become an effective analysis and decision means in any organization. The resource of the World Wide Web is almost infinite. The growing importance of electronic media for storing and disseminating text documents has created an urgent need for tools and techniques that assist users in finding and extracting relevant and previously unknown information from massive collection of documents available in the web. Thus the development of techniques for mining unstructured, semi-structured, and fully structured textual data has become quite important in both academia and industry. Information management of well organized databases has been a focus of the Data mining research. When to specify too many attributes, system will slow down thus exclude irrelevant or weakly relevant attributes. The general idea behind attribute relevance analysis is to compute some measure that is used to quantify the relevance of an attribute with respect to a given class or concept.

Related Content

Okure Udo Obot, Kingsley Friday Attai, Gregory O. Onwodi. © 2023. 28 pages.
Thomas M. Connolly, Mario Soflano, Petros Papadopoulos. © 2023. 29 pages.
Dmytro Dosyn. © 2023. 26 pages.
Jan Kalina. © 2023. 21 pages.
Avishek Choudhury, Mostaan Lotfalian Saremi, Estfania Urena. © 2023. 20 pages.
Yuanying Qu, Xingheng Wang, Limin Yu, Xu Zhu, Wenwu Wang, Zhi Wang. © 2023. 26 pages.
Yousra Kherabi, Damien Ming, Timothy Miles Rawson, Nathan Peiffer-Smadja. © 2023. 10 pages.
Body Bottom