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| Title Details: | |
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Knowledge Discovery from Data |
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| Authors: |
Kirkos, Efstathios |
| Reviewer: |
Symeonidis, Panagiotis |
| Description: | |
| Abstract: |
This chapter introduces students to the concepts of Knowledge Discovery from Data (KDD). It explains the reasons behind the emergence of this scientific field and refers to the disciplines on which KDD is based. The chapter presents various KDD tasks, such as association rule mining, classification, clustering, and others. The sequential stages of the knowledge discovery process are analyzed, including data cleaning, integration and transformation, knowledge extraction, and pattern evaluation. Finally, the chapter discusses the possibilities of knowledge extraction from different types of data, including relational databases, text, web data, and spatial databases.
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| Technical Editors: |
Papavasileiou, Spyridon |
| Type: |
Chapter |
| Creation Date: | 2015 |
| Item Details: | |
| License: |
http://creativecommons.org/licenses/by-nc-nd/3.0/gr |
| Handle | http://hdl.handle.net/11419/1233 |
| Bibliographic Reference: | Kirkos, E. (2015). Knowledge Discovery from Data [Chapter]. In Kirkos, E. 2015. Business Intelligence and Data Mining [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/1233 |
| Language: |
Greek |
| Is Part of: |
Business Intelligence and Data Mining |
| Publication Origin: |
Kallipos, Open Academic Editions |