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This book brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, this book will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field.
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mining complex data, output granularity, cousin pairs, graph kernels, cousin distance, logistic regression classifier, relevance feedback scheme, frequent subtrees, recall precision graphs, unlabeled data, sequence tagging, uninteresting rules, destination bytes, graph mining, concept drift, tree mining, incremental discovery, sequence mining, string kernels, specified time window, consensus trees, classifier error, streaming data, product graph, irrelevant images Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Data Alining, Morgan Kaufmann, Academic Press, Intl Conf, San Francisco, Data Engineering, San Diego, Travels Riyadh, Lecture Notes, Travels Cairo, Best Substructure Discovered, Columbia University, European Conference, Let Path, Proceedings of the Conference, Symbol Meaning New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
mining complex data, output granularity, cousin pairs, graph kernels, cousin distance, logistic regression classifier, relevance feedback scheme, frequent subtrees, recall precision graphs, unlabeled data, sequence tagging, uninteresting rules, destination bytes, graph mining, concept drift, tree mining, incremental discovery, sequence mining, string kernels, specified time window, consensus trees, classifier error, streaming data, product graph, irrelevant images Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Data Alining, Morgan Kaufmann, Academic Press, Intl Conf, San Francisco, Data Engineering, San Diego, Travels Riyadh, Lecture Notes, Travels Cairo, Best Substructure Discovered, Columbia University, European Conference, Let Path, Proceedings of the Conference, Symbol Meaning New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 23
books:
See all 23 books this book cites
3
books
cite this book:
- Data Mining by Jiawei Han on page 36, page 93, and page 150
- Advances in Kernel Methods: Support Vector Learning by Bernhard Schölkopf on page 73
- Relational Data Mining by Saso Dzeroski on page 93
- Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing) by K. C. Tan in Front Matter
- Environmental Online Communication by Arno Scharl in Front Matter
See all 23 books this book cites
- Machine Learning and Data Mining for Computer Security: Methods and Applications (Advanced Information and Knowledge Processing) by Marcus A. Maloof in Front Matter
- From Data and Information Analysis to Knowledge Engineering : Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University ... Data Analysis, and Knowledge Organization) by Myra Spiliopoulou on page 86
- Grey Information: Theory and Practical Applications (Advanced Information and Knowledge Processing) by Sifeng Liu in Front Matter
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