Автор: Leskovec Jure Название: Mining of Massive Datasets ISBN: 1108476341 ISBN-13(EAN): 9781108476348 Издательство: Cambridge Academ Рейтинг: Цена: 10771.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
Автор: Anand Sharma Название: Knowledge Engineering for Modern Information Systems ISBN: 3110713160 ISBN-13(EAN): 9783110713169 Издательство: Walter de Gruyter Рейтинг: Цена: 23049.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Knowledge Engineering (KE) is a fi eld within artifi cial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specifi c domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent fi ndings and innovative research in the information system and KE domain. Highlighting the challenges and diffi culties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will fi nd this book a valuable source of ideas and guidance.
Автор: Babo Rosalina, Dey Nilanjan, Ashour Amira S. Название: Workgroups Eassessment: Planning, Implementing and Analysing Frameworks ISBN: 9811599076 ISBN-13(EAN): 9789811599071 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book was developed during a particular pandemic situation in the whole world which confined people to their homes. This book provides a better understanding about the importance of teams` assessment and collaborative work, as well as the use of collaboration tools and online assessment techniques supported by technology.
Название: Research 2.0 and the impact of digital technologies on scholarly inquiry / ISBN: 1522508309 ISBN-13(EAN): 9781522508304 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 18919.00 р. 27027.00-30% Наличие на складе: Есть (1 шт.) Описание: The academic landscape has been significantly enhanced by the advent of new technology. These tools allow researchers easier information access to better increase their knowledge base.Research 2.0 and the Impact of Digital Technologies on Scholarly Inquiry is an authoritative reference source for the latest insights on the impact of web services and social technologies for conducting academic research. Highlighting international perspectives, emerging scholarly practices, and real-world contexts, this book is ideally designed for academicians, practitioners, upper-level students, and professionals interested in the growing field of digital scholarship.
Автор: Del Giudice, Manlio (link Campus University, Italy Название: Knowledge management and ai in society 5.0 ISBN: 1032191910 ISBN-13(EAN): 9781032191911 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores and offers an overview of knowledge management embraced in the current scenario of Society 5.0, shedding light on its importance in a society that is increasingly digital and interconnected.
Описание: This book presents a theoretical critical appraisal of the Mechanistic Theory of Human Cognition (MTHC), which is one of the most popular major theories in the contemporary field of cognitive science.
Автор: Tiwari, Sanju Название: Semantic AI in Knowledge Graphs ISBN: 1032321857 ISBN-13(EAN): 9781032321851 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency and integrating knowledge bases. It provides the mathematical background to solve problems of restoring consistency and problems of integrating probabilistic knowledge bases.
Автор: Charu C. Aggarwal Название: Machine Learning for Text ISBN: 3030088073 ISBN-13(EAN): 9783030088071 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories:- Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for machine learning from text such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.- Domain-sensitive mining: Chapters 8 and 9 discuss the learning methods from text when combined with different domains such as multimedia and the Web. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. - Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning (with text as a backdrop). This textbook targets graduate students in computer science, as well as researchers, professors, and industrial practitioners working in these related fields. This textbook is accompanied with a solution manual for classroom teaching.
Автор: Madria Название: Big Data Analytics and Knowledge Discovery ISBN: 3319439456 ISBN-13(EAN): 9783319439457 Издательство: Springer Рейтинг: Цена: 8106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.
Автор: Tao Li; Mitsunori Ogihara; George Tzanetakis Название: Music Data Mining ISBN: 1439835527 ISBN-13(EAN): 9781439835524 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing.
The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining.
The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
Автор: Bergman, Michael K. Название: A knowledge representation practionary ISBN: 3319980912 ISBN-13(EAN): 9783319980911 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy.
Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI.
This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles.
This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative.
This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.
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