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Biologically-Inspired Techniques for Knowledge Discovery and Data Mining

increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data;

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Trends and Applications in Knowledge Discovery and Data Mining

were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2016 include: Biologically Inspired Data Mining;

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Trends and Applications in Knowledge Discovery and Data Mining

(MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI;

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Trends and Applications in Knowledge Discovery and Data Mining

Decision Analytics for Public Health and Wellness, DMDA-Health; Biologically Inspired Data Mining Techniques, BDM; Mobile Data Management, Mining;

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Trends and Applications in Knowledge Discovery and Data Mining

) * Learning Data Representation for Clustering (LDRC 2020) * Ninth Workshop on Biologically Inspired Techniques for Data Mining (BDM;

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Trends and Applications in Knowledge Discovery and Data Mining

on Biologically-inspired Techniques for Knowledge Discovery and Data Mining * DLKT 2019: 1st Pacific Asia Workshop on Deep;

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Service-Oriented Distributed Knowledge Discovery

unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures;

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Service-Oriented Distributed Knowledge Discovery

unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures;

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Data Mining Methods for Knowledge Discovery

chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate;

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Data Mining and Knowledge Discovery for Geoscientists

poor knowledge". The true solution is to apply data mining techniques in geosciences databases and to modify these techniques for;

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Implementations and Applications of Machine Learning

mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including;

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Implementations and Applications of Machine Learning

mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including;

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Data Mining in Bioinformatics

mining, gene mapping for disease detection, and phylogenetic knowledge discovery.;

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Geographic Data Mining and Knowledge Discovery

first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and;

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Hybrid Artificial Intelligent Systems

. They are organized in the following topical sections: data mining, knowledge discovery and big data; bio-inspired models and evolutionary;

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Knowledge Discovery in the Social Sciences

methods-the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge;

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Knowledge Discovery in the Social Sciences

methods-the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge;

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Advanced Data Mining

implementations of knowledge discovery and data mining. It may appear that the same things are being repeated but in general, same approach and techniques;

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Knowledge Discovery Process and Methods to Enhance Organizational Performance

Methods to Enhance Organizational Performance explains the knowledge discovery and data mining (KDDM) process in a manner that makes it easy for;

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Data Mining

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge;

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Pharmaceutical Data Mining

industry. Focusing on diverse data mining approaches for drug discovery, including chemogenomics, toxicogenomics, and individual drug response;

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Knowledge Discovery in Multiple Databases

framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning;

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Data Warehousing and Knowledge Discovery

tools, data warehouse performance and optimization, pattern mining, matrix-based mining techniques and stream, sensor and time-series mining.;

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Hybrid Artificial Intelligent Systems

submissions. The papers are grouped into these topics: advanced data processing and visualization techniques; bio-inspired models and optimization;

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New Frontiers in Applied Data Mining

workshopsorganized along with the main 2008 Paci?c Asia Conference on Knowledge Discovery and Data Mining (PAKDD) in Osaka, Japan was to extend the;

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Multimedia Data Mining

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines;

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Multimedia Data Mining

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines;

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