Trends and Applications in Knowledge Discovery and Data Mining, Mohadeseh Ganji; Lida Rashidi; Benjamin C. M. Fung
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: Leong Hou U.; Hady W. Lauw Название: Trends and Applications in Knowledge Discovery and Data Mining ISBN: 3030261417 ISBN-13(EAN): 9783030261412 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019).- A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045.- An Investigation on Multi View based User Behavior towards Spam Detection in Social Networks.- A Cluster Ensemble Strategy for Asian Handicap Betting.- Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example.- Early Churn User Classification in Social Networking Service Using Attention-based Long Short-Term Memory.- PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019).- Weakly Supervised Learning by a Confusion Matrix of Contexts.- Learning a Semantic Space for Modeling Images, Tags and Feelings in Cross-media Search.- Adversarial Active Learning in the Presence of Weak and Malicious Oracles.- The Most Related Knowledge First: A Progressive Domain Adaptation Method.- Learning Data Representation for Clustering (LDRC 2019).- Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps.- Deep cascade of extra trees.- Algorithms for an Efficient Tensor Biclustering.- Change point detetion in periodic panel data using a mixture-model-based approach.- The 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining (BDM 2019).- Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification.- Protein Complexes Detection Based on Deep Neural Network.- Predicting Auction Price of Vehicle License Plate with Deep Residual Learning.- Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions.- Chinese Word Segmentation with Feature Alignment.- Spike Sorting with Locally Weighted Co-association Matrix-based Spectral Clustering.- Label Distribution Learning Based Age-Invariant Face Recognition.- Overall Loss For Deep Neural Networks.- Sentiment Analysis Based on LSTM Architecture with Emoticon Attention.- Aspect Level Sentiment Analysis with Aspect Attention.- The 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer (DLKT 2019).- Transfer Channel Pruning for Compressing Deep Domain Adaptation Models.- A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting.- Natural Language Business Intelligence Question Answering through SeqtoSeq Transfer Learning.- Robust Faster R-CNN: Increasing Robustness to Occlusions and multi-scale objects.- Effectively Representing Short Text via the Improved Semantic Feature Space Mapping.- Probabilistic Graphical Model Based Highly Scalable Directed Community Detection Algorithm.- Hilltop based recommendation in co-author networks.- Neural Variational Collaborative Filtering for Top-K Recommendation.
Автор: Chu Wesley W. Название: Data Mining and Knowledge Discovery for Big Data ISBN: 3642408362 ISBN-13(EAN): 9783642408366 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.
Описание: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery.
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.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Pradeep Kumar, P. Radha Krishna, S. Bapi Raju Название: Pattern Discovery Using Sequence Data Mining: Applications and Studies ISBN: 1613500564 ISBN-13(EAN): 9781613500569 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Pattern Discovery Using Sequence Data Mining: Applications and Studies provides a comprehensive view of sequence mining techniques and presents current research and case studies in pattern discovery in sequential data by researchers and practitioners. This research identifies industry applications introduced by various sequence mining approaches.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations of Data Mining and Knowledge Discovery ISBN: 3540262571 ISBN-13(EAN): 9783540262572 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.
Описание: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications.
Автор: Takashi Washio; Einoshin Suzuki; Kai Ming Ting; Ak Название: Advances in Knowledge Discovery and Data Mining ISBN: 3540681248 ISBN-13(EAN): 9783540681243 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 12th Pacific-Asia Conference PAKDD 2008 Osaka Japan May 20-23 2008 Proceedings.
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.
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