Next Generation Knowledge Machines Book

Next Generation Knowledge Machines

  • Author : Syed V. Ahamed
  • Publisher : Elsevier
  • Release Date : 2013-09-13
  • Genre: Computers
  • Pages : 336
  • ISBN 10 : 9780124166691

Next Generation Knowledge Machines Excerpt :

This book delivers the scientific and mathematical basis to treat and process knowledge as a quantifiable and dimensioned entity. It provides the units and measures for the value of information contained in a "body of knowledge" that can be measured, processed, enhanced, communicated and preserved. It provides a basis to evaluate the quantity of knowledge acquired by students at various levels and in different universities. The effect of time on the dynamics and flow of knowledge is tied to Internet knowledge banks and provides the basis for designing and building the next generation of novel machine to appear in society. This book ties the basic needs of all human beings to the modern machines that resolve such need based on Internet knowledge banks (KBs) distributed throughout nations and societies. The features of the Intelligent Internet are fully exploited to make a new generation of students and knowledge workers use the knowledge resources elegantly and optimally. It deals with topics and insight into the design and architecture of next-generation computing systems that deal with human and social problems. Processor and Internet technologies that have already revolutionized human lives form the subject matter and the focal point of this book. Information and knowledge on the Internet delivered by next-generation mobile networks form the technical core presented. Human thought processes and adjustments follow the solutions offered by machines. Extends the established practices and designs documented in computer systems to encompass the evolving knowledge processing field Provides an academic and industrial viewpoint of the concurrent dynamic changes in computer and communication industries Presents information for all perspectives, from managers, scientists and researchers Basic concepts can be applied to other disciplines and situations

Next Generation Machine Learning with Spark Book

Next Generation Machine Learning with Spark

  • Author : Butch Quinto
  • Publisher : Apress
  • Release Date : 2020-02-22
  • Genre: Computers
  • Pages : 355
  • ISBN 10 : 9781484256695

Next Generation Machine Learning with Spark Excerpt :

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.xAchieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM librariesDetect anomalies with the Isolation Forest algorithm for SparkUse the Spark NLP and Stanford CoreNLP libraries that support multiple languagesOptimize your ML workload with the Alluxio in-memory data accelerator for SparkUse GraphX and GraphFrames for Graph AnalysisPerform image recognition using convolutional neural networksUtilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.

Evolution of Knowledge Science Book

Evolution of Knowledge Science

  • Author : Syed V. Ahamed
  • Publisher : Morgan Kaufmann
  • Release Date : 2016-10-25
  • Genre: Computers
  • Pages : 578
  • ISBN 10 : 9780128093559

Evolution of Knowledge Science Excerpt :

Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines explains how to design and build the next generation of intelligent machines that solve social and environmental problems in a systematic, coherent, and optimal fashion. The book brings together principles from computer and communication sciences, electrical engineering, mathematics, physics, social sciences, and more to describe computer systems that deal with knowledge, its representation, and how to deal with knowledge centric objects. Readers will learn new tools and techniques to measure, enhance, and optimize artificial intelligence strategies for efficiently searching through vast knowledge bases, as well as how to ensure the security of information in open, easily accessible, and fast digital networks. Author Syed Ahamed joins the basic concepts from various disciplines to describe a robust and coherent knowledge sciences discipline that provides readers with tools, units, and measures to evaluate the flow of knowledge during course work or their research. He offers a unique academic and industrial perspective of the concurrent dynamic changes in computer and communication industries based upon his research. The author has experience both in industry and in teaching graduate level telecommunications and network architecture courses, particularly those dealing with applications of networks in education. Presents a current perspective of developments in central, display, signal, and graphics processor-units as they apply to designing knowledge systems Offers ideas and methodologies for systematically extending data and object processing in computing into other disciplines such as economics, mathematics, and management Provides best practices and designs for engineers alongside case studies that illustrate practical implementation ideas across multiple domains

Knowledge Machines Book

Knowledge Machines

  • Author : Eric T. Meyer
  • Publisher : MIT Press
  • Release Date : 2015-04-03
  • Genre: Language Arts & Disciplines
  • Pages : 288
  • ISBN 10 : 9780262028745

Knowledge Machines Excerpt :

An examination of the ways that digital and networked technologies have fundamentally changed research practices in disciplines from astronomy to literary analysis. In Knowledge Machines, Eric Meyer and Ralph Schroeder argue that digital technologies have fundamentally changed research practices in the sciences, social sciences, and humanities. Meyer and Schroeder show that digital tools and data, used collectively and in distributed mode—which they term e-research—have transformed not just the consumption of knowledge but also the production of knowledge. Digital technologies for research are reshaping how knowledge advances in disciplines that range from physics to literary analysis. Meyer and Schroeder map the rise of digital research and offer case studies from many fields, including biomedicine, social science uses of the Web, astronomy, and large-scale textual analysis in the humanities. They consider such topics as the challenges of sharing research data and of big data approaches, disciplinary differences and new forms of interdisciplinary collaboration, the shifting boundaries between researchers and their publics, and the ways that digital tools promote openness in science. This book considers the transformations of research from a number of perspectives, drawing especially on the sociology of science and technology and social informatics. It shows that the use of digital tools and data is not just a technical issue; it affects research practices, collaboration models, publishing choices, and even the kinds of research and research questions scholars choose to pursue. Knowledge Machines examines the nature and implications of these transformations for scholarly research.

Next Generation Business Intelligence Book

Next Generation Business Intelligence

  • Author : Sonar, Rajendra M.
  • Publisher : Vikas Publishing House
  • Release Date : 2022-07-01
  • Genre: Uncategoriezed
  • Pages : null
  • ISBN 10 : 9788125942566

Next Generation Business Intelligence Excerpt :

Business Intelligence (BI) has been successfully deployed by modern businesses to serve their customers and stakeholders. However, organizations increasingly look at BI to be all pervasive and realize its higher level of potential, instead of following it conventionally. The book covers the techniques, technologies and frameworks that can be used to build next generation BI.

Intelligent Internet Knowledge Networks Book
Score: 5
From 1 Ratings

Intelligent Internet Knowledge Networks

  • Author : Syed V. Ahamed
  • Publisher : John Wiley & Sons
  • Release Date : 2006-11-17
  • Genre: Computers
  • Pages : 520
  • ISBN 10 : 9780470055984

Intelligent Internet Knowledge Networks Excerpt :

Introducing the basic concepts in total program control of the intelligent agents and machines, Intelligent Internet Knowledge Networks explores the design and architecture of information systems that include and emphasize the interactive role of modern computer/communication systems and human beings. Here, you’ll discover specific network configurations that sense environments, presented through case studies of IT platforms, electrical governments, medical networks, and educational networks.

Computational Framework for Knowledge Book

Computational Framework for Knowledge

  • Author : Syed V. Ahamed
  • Publisher : John Wiley & Sons
  • Release Date : 2009-07-31
  • Genre: Technology & Engineering
  • Pages : 500
  • ISBN 10 : 0470480416

Computational Framework for Knowledge Excerpt :

"Intriguing . . . [filled with] new ideas about overarching intellectual themes that govern our technologies and our society." —Nikil Jayant, Eminent Scholar, Georgia Research Alliance "Dr. Ahamed is correct in observing that 'silicon and glass have altered the rhythm of mind' and that computers need to be more 'human.'" —Bishnu S. Atal, Member, National Academy of Engineering This book combines philosophical, societal, and artificial intelligence concepts with those of computer science and information technology to demonstrate novel ways in which computers can simplify data mining on the Internet. It describes numerous innovative methods that go well beyond information retrieval to allow computers to accomplish such tasks as processing, classifying, prioritizing, and reconstituting knowledge. The book is divided into five parts: New knowledge sensing and filtering environments Concept building and wisdom machines General structure and theory of knowledge Verb functions and noun objects Humanistic and semi-human systems This book offers new mathematical methodologies and concrete HW/SW/FW configurations for the IT specialist to help their corporations explore, exploit, compete, and win global market share.

The Knowledge Machine  How Irrationality Created Modern Science Book
Score: 3
From 1 Ratings

The Knowledge Machine How Irrationality Created Modern Science

  • Author : Michael Strevens
  • Publisher : Liveright Publishing
  • Release Date : 2020-10-13
  • Genre: Science
  • Pages : 368
  • ISBN 10 : 9781631491382

The Knowledge Machine How Irrationality Created Modern Science Excerpt :

“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the gr

Emanuel Goldberg and His Knowledge Machine Book

Emanuel Goldberg and His Knowledge Machine

  • Author : Michael Keeble Buckland
  • Publisher : Greenwood Publishing Group
  • Release Date : 2006
  • Genre: Fiction
  • Pages : 380
  • ISBN 10 : 0313313326

Emanuel Goldberg and His Knowledge Machine Excerpt :

A fascinating and illuminating tribute to a great mind and a crucial period in the history of information science and technology.

Next Generation of Data Mining Book
Score: 4
From 1 Ratings

Next Generation of Data Mining

  • Author : Hillol Kargupta
  • Publisher : CRC Press
  • Release Date : 2008-12-24
  • Genre: Computers
  • Pages : 601
  • ISBN 10 : 1420085875

Next Generation of Data Mining Excerpt :

Drawn from the US National Science Foundation’s Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field. Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Cognitive Engineering for Next Generation Computing Book

Cognitive Engineering for Next Generation Computing

  • Author : Kolla Bhanu Prakash
  • Publisher : John Wiley & Sons
  • Release Date : 2021-04-06
  • Genre: Computers
  • Pages : 368
  • ISBN 10 : 9781119711087

Cognitive Engineering for Next Generation Computing Excerpt :

The cognitive approach to the IoT provides connectivity to everyone and everything since IoT connected devices are known to increase rapidly. When the IoT is integrated with cognitive technology, performance is improved, and smart intelligence is obtained. Discussed in this book are different types of datasets with structured content based on cognitive systems. The IoT gathers the information from the real time datasets through the internet, where the IoT network connects with multiple devices. This book mainly concentrates on providing the best solutions to existing real-time issues in the cognitive domain. Healthcare-based, cloud-based and smart transportation-based applications in the cognitive domain are addressed. The data integrity and security aspects of the cognitive computing main are also thoroughly discussed along with validated results.

The Development of Natural Language Processing Book

The Development of Natural Language Processing

  • Author : China Info & Comm Tech Grp Corp
  • Publisher : Springer Nature
  • Release Date : 2021-06-09
  • Genre: Computers
  • Pages : 83
  • ISBN 10 : 9789811619861

The Development of Natural Language Processing Excerpt :

This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China”, which explores the cutting edge of natural language processing (NLP) studies. The research objects of natural language processing are evolved from words, phrases, and sentences to text, and research directions are from language analysis, language understanding, language generation, knowledge graphs, machine translation, to deep semantic understanding, and beyond. This is in line with the development trend of applications. And for another typical NLP application machine translation, from text translation, to voice and image translation, now simultaneous interpretation, progress of technology makes the application of machine translation deeper and wider into diverse industries. This book is intended for researchers and industrial staffs who have been following the current situation and future trends of the natural language processing. Meanwhile, it also bears high value of reference for experts, scholars, and technical and engineering managers of different levels and different fields.

Machine Learning and Knowledge Discovery in Databases Book

Machine Learning and Knowledge Discovery in Databases

  • Author : Walter Daelemans
  • Publisher : Springer
  • Release Date : 2008-08-17
  • Genre: Computers
  • Pages : 692
  • ISBN 10 : 9783540874799

Machine Learning and Knowledge Discovery in Databases Excerpt :

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

Machine Learning and Knowledge Discovery in Databases Book

Machine Learning and Knowledge Discovery in Databases

  • Author : Frank Hutter
  • Publisher : Springer Nature
  • Release Date : 2021-02-24
  • Genre: Computers
  • Pages : 764
  • ISBN 10 : 9783030676582

Machine Learning and Knowledge Discovery in Databases Excerpt :

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.

Machine Learning and Knowledge Discovery in Databases  Applied Data Science Track Book

Machine Learning and Knowledge Discovery in Databases Applied Data Science Track

  • Author : Yuxiao Dong
  • Publisher : Springer Nature
  • Release Date : 2021-09-09
  • Genre: Computers
  • Pages : 554
  • ISBN 10 : 9783030865146

Machine Learning and Knowledge Discovery in Databases Applied Data Science Track Excerpt :

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.