Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery, Kovalerchuk

Автор: Michele Berlingerio; Francesco Bonchi; Thomas G?rt
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3030109275 ISBN-13(EAN): 9783030109271
Издательство: Springer
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Цена: 93160.00 T
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Описание: The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. Part III: ADS data science applications;

Автор: Chesterman Simon
Название: We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law
ISBN: 1316517683 ISBN-13(EAN): 9781316517680
Издательство: Cambridge Academ
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Цена: 38010.00 T
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Описание: Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed.

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
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Цена: 46570.00 T
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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: Ulf Brefeld; Edward Curry; Elizabeth Daly; Brian M
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3030109968 ISBN-13(EAN): 9783030109967
Издательство: Springer
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Цена: 46570.00 T
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Описание: The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. and transfer learning. Part III: ADS data science applications;

Автор: Kovalerchuk
Название: Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery
ISBN: 3030931188 ISBN-13(EAN): 9783030931186
Издательство: Springer
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Цена: 149060.00 T
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Описание: This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.

Автор: Jude Hemanth; Madhulika Bhatia; Oana Geman
Название: Data Visualization and Knowledge Engineering
ISBN: 3030257967 ISBN-13(EAN): 9783030257965
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats. Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role. Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field. Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.

Автор: Michael L. Brodie; John Mylopoulos
Название: On Knowledge Base Management Systems
ISBN: 1461293839 ISBN-13(EAN): 9781461293835
Издательство: Springer
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Цена: 81050.00 T
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Описание: Current experimental systems in industry, government, and the military take advantage of knowledge-based processing. Currently, knowledge-based system technology lacks the means to provide efficient and robust knowledge bases, while database system technology lacks knowledge representation and reasoning capabilities.

Автор: Tapio Elomaa; Heikki Mannila; Hannu Toivonen
Название: Principles of Data Mining and Knowledge Discovery
ISBN: 3540440372 ISBN-13(EAN): 9783540440376
Издательство: Springer
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Цена: 74530.00 T
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Описание: Constitutes the proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery held in Finland in 2002. Papers cover kernel methods, probabilistic methods, association rule mining, rough sets, sampling algorithms, pattern discovery, web text mining and more.

Автор: Xindong Wu; Ramamohanarao Kotagiri; Kevin B. Korb
Название: Research and Development in Knowledge Discovery and Data Mining
ISBN: 3540643834 ISBN-13(EAN): 9783540643838
Издательство: Springer
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Цена: 81050.00 T
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Описание: This collection of papers contributes results to all aspects in knowledge discovery and data mining on the research level as well as on machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software re-engineering, and knowledge-based systems.

Автор: Phung
Название: Advances in Knowledge Discovery and Data Mining
ISBN: 3319930338 ISBN-13(EAN): 9783319930336
Издательство: Springer
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Цена: 83850.00 T
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Описание: This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018.

Автор: Qiang Yang; Zhi-Hua Zhou; Zhiguo Gong; Min-Ling Zh
Название: Advances in Knowledge Discovery and Data Mining
ISBN: 3030161412 ISBN-13(EAN): 9783030161415
Издательство: Springer
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Цена: 76390.00 T
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Описание: The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions.

Автор: Jan M. Zytkow; Mohamed Quafafou
Название: Principles of Data Mining and Knowledge Discovery
ISBN: 3540650687 ISBN-13(EAN): 9783540650683
Издательство: Springer
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Цена: 83850.00 T
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Описание: The refereed proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery. There are 26 revised papers and 30 poster presentations organized in topical sections, including rule evaluation, visualization, association rules and text mining, and tree construction.