The Best-Known Algorithms Currently Used in the datamining CommunityContributions from recognized leaders in the fieldIdentifying some of the most influential algorithms that are widely used in the datamining commun...
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ISBN:
(数字)9781420089653
ISBN:
(纸本)9781420089646
The Best-Known Algorithms Currently Used in the datamining CommunityContributions from recognized leaders in the fieldIdentifying some of the most influential algorithms that are widely used in the datamining community, The Top Ten Algorithms in datamining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or world-class researchers who have extensively studied the respective *** book concentrates on the following important algorithms: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Examples illustrate how each algorithm works and highlight its overall performance in a real-world application. The text covers key topics—including classification, clustering, statistical learning, association analysis, and link mining—in datamining research and development as well as in datamining, machine learning, and artificial intelligence *** naming the leading algorithms in this field, this book encourages the use of datamining techniques in a broader realm of real-world applications. It should inspire more datamining researchers to further explore the impact and novel research issues of these algorithms.
Drawn from the US National Science Foundations Symposium on Next Generation of datamining and Cyber-Enabled discovery for Innovation (NGDM 07), Next Generation of datamining explores emerging technologies and applic...
ISBN:
(纸本)9781420085860
Drawn from the US National Science Foundations Symposium on Next Generation of datamining and Cyber-Enabled discovery for Innovation (NGDM 07), Next Generation of datamining explores emerging technologies and applications in datamining as well as potential challenges faced by the field. Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of datamining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance datamining. They also discuss the impact of new technologies, such as the semantic web, on datamining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for datamining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to datamining problems that span an array of disciplines.
Collecting the latest developments in the field, Multimedia datamining: A Systematic Introduction to Concepts and Theory defines multimedia datamining, its theory, and its applications. Two of the most active resear...
ISBN:
(纸本)9781584889663;1584889667
Collecting the latest developments in the field, Multimedia datamining: A Systematic Introduction to Concepts and Theory defines multimedia datamining, its theory, and its applications. Two of the most active researchers in multimedia datamining explore how this young area has rapidly developed in recent years. The book first discusses the theoretical foundations of multimedia datamining, presenting commonly used feature representation, knowledge representation, statistical learning, and soft computing techniques. It then provides application examples that showcase the great potential of multimedia datamining technologies. In this part, the authors show how to develop a semantic repository training method and a concept discovery method in an imagery database. They demonstrate how knowledgediscovery helps achieve the goal of imagery annotation. The authors also describe an effective solution to large-scale video search, along with an application of audio data classification and categorization. This novel, self-contained book examines how the merging of multimedia and datamining research can promote the understanding and advance the development of knowledgediscovery in multimedia data.
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