Soft Computing for Knowledge Discovery and Data Mining, Oded Maimon; Lior Rokach
Автор: James G. Shanahan Название: Soft Computing for Knowledge Discovery ISBN: 0792379187 ISBN-13(EAN): 9780792379188 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Knowledge discovery is an area of computer science that attempts to uncover interesting patterns in data that permit a computer to perform a task autonomously. This title provides a self-contained exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective.
Автор: Evangelos Triantaphyllou Название: Data Mining and Knowledge Discovery via Logic-Based Methods ISBN: 1441916296 ISBN-13(EAN): 9781441916297 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.
Автор: Evangelos Triantaphyllou Название: Data Mining and Knowledge Discovery via Logic-Based Methods ISBN: 1461426138 ISBN-13(EAN): 9781461426134 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.
Описание: 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.
Описание: Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery.Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Описание: This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2016, held in conjunction with PAKDD, the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented were carefully reviewed and selected from 38 submissions.
Автор: U Kang; Ee-Peng Lim; Jeffrey Xu Yu; Yang-Sae Moon Название: Trends and Applications in Knowledge Discovery and Data Mining ISBN: 3319672738 ISBN-13(EAN): 9783319672731 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The workshops affiliated with PAKDD 2017 include: Workshop on Machine Learning for Sensory Data Analysis (MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI), and Workshop on Data Mining in Business Process Management (DM-BPM).
Автор: Vincent S. Tseng; Tu Bao Ho; Zhi-Hua Zhou; Arbee L Название: Advances in Knowledge Discovery and Data Mining ISBN: 3319066072 ISBN-13(EAN): 9783319066073 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. They cover the general fields of pattern mining; graph and network mining; biomedical data mining; and unstructured data and text mining.
Автор: Mohamed Medhat Gaber Название: Scientific Data Mining and Knowledge Discovery ISBN: 3642426247 ISBN-13(EAN): 9783642426247 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the reader with a complete view of the different tools used in the analysis of data for scientific discovery. The book offers both an overview of the state-of-the-art, and lists areas and open issues for future research and development.
Автор: Wen-Chih Peng; Haixun Wang; James Bailey; Vincent Название: Trends and Applications in Knowledge Discovery and Data Mining ISBN: 3319131850 ISBN-13(EAN): 9783319131856 Издательство: Springer Рейтинг: Цена: 13416.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings at PAKDD Workshops 2014, held in conjunction with the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and selected from 179 submissions.
Автор: Tru Cao; Ee-Peng Lim; Zhi-Hua Zhou; Tu-Bao Ho; Dav Название: Advances in Knowledge Discovery and Data Mining ISBN: 3319180312 ISBN-13(EAN): 9783319180311 Издательство: Springer Рейтинг: Цена: 12298.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This two-volume set, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and selected from 405 submissions.
Описание: Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions.- Visual Data Mining: Effective Exploration of the Biological Universe.- Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining.- On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process.- Adapted Features and Instance Selection for Improving Co-training.- Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System.- On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics.- A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data.- Interactive Data Exploration Using Pattern Mining.- Resources for Studying Statistical Analysis of Biomedical Data and R.- A Kernel-Based Framework for Medical Big-Data Analytics.- On Entropy-Based Data Mining.- Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure.- Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges.- Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine.- Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges.- Protecting Anonymity in Data-Driven Biomedical Science.- Biobanks - A Source of Large Biological Data Sets: Open Problems and Future Challenges.- On Topological Data Mining.
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