Biologically-Inspired Techniques for Knowledge Discovery and Data Mining by Shafiq Alam
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.-
Intelligent Multidimensional Data Clustering and Analysis
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Emerging Methods in Predictive Analytics
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Innovative Techniques and Applications of Entity Resolution
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Graph Data Management
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Data Mining and Analysis in the Engineering Field
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XML Data Mining
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Design, Performance, and Analysis of Innovative Information Retrieval
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Intelligent Techniques for Data Analysis in Diverse Settings
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Handbook of Research on Big Data Management and Applications
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Data Mining Trends and Applications in Criminal Science and Investigations
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Web Usage Mining Techniques and Applications Across Industries
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Collaborative Filtering Using Data Mining and Analysis
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Social Media Data Extraction and Content Analysis
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Mobile Technologies for Activity-Travel Data Collection and Analysis
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Web Semantics for Textual and Visual Information Retrieval
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Knowledge Discovery Practices and Emerging Applications of Data Mining
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Emerging Trends in the Development and Application of Composite Indicators
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Web Data Mining and the Development of Knowledge-Based Decision Support Systems
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Data Mining in Public and Private Sectors
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Innovative Document Summarization Techniques
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Data Science and Simulation in Transportation Research
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Data Visualization and Statistical Literacy for Open and Big Data
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Data Mining in Dynamic Social Networks and Fuzzy Systems
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Advancing Cloud Database Systems and Capacity Planning with Dynamic Applications
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Innovative Approaches of Data Visualization and Visual Analytics
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Advanced Database Query Systems
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Exploring the Convergence of Big Data and the Internet of Things
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Text Mining Techniques for Healthcare Provider Quality Determination
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Big Data Management, Technologies, and Applications
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Ethical Data Mining Applications for Socio-Economic Development
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Managing and Processing Big Data in Cloud Computing
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Handbook of Research on Innovative Database Query Processing Techniques
The Minerals, Metals & Materials Society (TMS) is a member-driven international professional society dedicated to fostering the exchange of learning and ideas across the entire range of materials science and engineering, from minerals processing and primary metals production, to basic research and the advanced applications of materials. Included among its nearly 13,000 professional and student members are metallurgical and materials engineers, scientists, researchers, educators, and administrators from more than 70 countries on six continents.
| SKU | Unavailable |
| ISBN 13 | 9781466660786 |
| ISBN 10 | 1466660783 |
| Title | Biologically-Inspired Techniques for Knowledge Discovery and Data Mining |
| Author | Shafiq Alam |
| Series | Advances In Data Mining And Database Management |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Idea Group,U.S. |
| Year published | 2014-05-31 |
| Number of pages | 375 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |