Biologically-inspired techniques for knowledge discovery and data mining

Shafiq Alam (Editor), Gillian Dobbie (Editor), Yun Sing Koh (Editor), Saeed Ur Rehman (Editor)

Research output: Book/ReportAnthologypeer-review

2 Citations (Scopus)


Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.

Original languageEnglish
Place of PublicationHershy, PA
PublisherIGI Global
Number of pages375
ISBN (Electronic)9781466660793
ISBN (Print)1466660783, 9781466660786
Publication statusPublished - 31 May 2014
Externally publishedYes

Publication series

NameAdvances in Data Mining and Database Management
PublisherIGI Global
ISSN (Print)2327-1981
ISSN (Electronic)2327-199X


  • Data mining
  • Knowledge Discovery


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