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Data Mining and Knowledge Discovery

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Springer Handbook of Geographic Information

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Abstract

In this chapter, data mining and knowledge discovery (DMKD) is presented with basic concepts, a brief history of its evolution, mathematical foundations, and usable techniques, along with the data warehouse and the decision support system (DSS). First, dataset and knowledge will be defined and elucidated as under DMKD. DMKD is a discovery process with different hierarchies, granularities, and/or scales. For a set of concepts that may be best understood if being viewed and explained from various perspectives, the chapter starts with a definition followed by a table explaining DMKD from different views (Sect. 5.1). The evolution of DMKD is then briefly tracked from the rapid advance in massive data to the birth of DMKD (Sect. 5.2). Some mathematical foundations are given in Sect. 5.3, i.e. probability theory, statistics, fuzzy set, rough set, data fields, and cloud models. Section 5.4 introduces some usable DMKD techniques. DMKD is used to discover a set of rules and exceptions with association, classification, clustering, prediction, discrimination, and exception detection. In Sects. 5.5 and 5.6, data warehouses and decision support systems are given. The first one mentioned is one of the data sources for DMKD, and DMKD is a new technique to assist the latter with a task. Finally, trends and perspectives are summarized and forecasted into two promising fields, web mining and spatial data mining (Sect. 5.7).

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Abbreviations

BI:

business intelligence

DBMS:

database management system

DMKD:

data mining and knowledge discovery

DSS:

decision support system

ERP:

enterprise resource planning

ETL:

extraction, transformation, and loading

GIS:

Geographic Information System

GNSS:

Global Navigation Satellite System

HTML:

Hypertext Markup Language

OLAP:

Online analytical processing

OLTP:

online transactional processing

RS:

remote sensing

SDMKD:

spatial data mining and knowledge discovery

SDSS:

spatial decision support system

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Author information

Authors and Affiliations

  1. International School of Software, Wuhan University, 129 Luoyu Road, 430079, Wuhan, Hubei, China

    Shuliang Wang

  2. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Wenzhong Shi

Authors
  1. Shuliang Wang
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  2. Wenzhong Shi
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Corresponding authors

Correspondence to Shuliang Wang or Wenzhong Shi .

Editor information

Editors and Affiliations

  1. University of Applied Sciences Neubrandenburg, Brodaer Str. 2, 17033, Neubrandenburg, Germany

    Wolfgang Kresse

  2. Environmental Systems Research Institute, Inc., 8615 Westwood Center Drive, 22182-2214, Vienna, VA, USA

    David M. Danko

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Wang, S., Shi, W. (2011). Data Mining and Knowledge Discovery. In: Kresse, W., Danko, D. (eds) Springer Handbook of Geographic Information. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72680-7_5

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