Information Computing and Applications, Part II
Information Computing and Applications, Part II

Author: Rongbo Zhu

Publisher: Springer

Published: 2010-09-30

Total Pages: 556

ISBN-13: 3642163394

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This volume contains the proceedings of the International Conference on Inf- mation Computing and Applications (ICICA 2010), which was held in Tangshan, China, October 15-18, 2010. As future-generation information technology, information computing and applications become specialized, information computing and applications - cluding hardware, software, communications and networks are growing with ever-increasing scale and heterogeneity and becoming overly complex. The c- plexity is getting more critical along with the growing applications. To cope with the growing and computing complexity, information computing and applications focus on intelligent, selfmanageable, scalable computing systems and applications to the maximum extent possible without human intervention or guidance. With the rapid development of information science and technology, infor- tion computing has become the third approach of science research. Information computing and applications is the ?eld of study concerned with constructing - telligent computing, mathematical models, numerical solution techniques and using computers to analyze and solve natural scienti?c, social scienti?c and engineering problems. In practical use, it is typically the application of c- puter simulation, intelligent computing, internet computing, pervasive comp- ing, scalable computing, trusted computing, autonomy-oriented computing, evolutionary computing, mobile computing, computational statistics, engine- ing computing, multimedia networking and computing, applications and other forms of computation problems in various scienti?c disciplines and engine- ing. Information computing and applications is an important underpinning for techniques used in information and computational science and there are many unresolved problems that address worth studying.

Information Computing and Applications
Information Computing and Applications

Author: Baoxiang Liu

Publisher: Springer

Published: 2012-09-07

Total Pages: 800

ISBN-13: 3642340628

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This book constitutes the refereed proceedings of the Third International Conference on Information Computing and Applications, ICICA 2012, held in Chengde, China, in September 2012. The 100 revised full papers were carefully reviewed and selected from 1089 submissions. The papers are organized in topical sections on internet computing and applications, multimedia networking and computing, intelligent computing and applications, computational statistics and applications, cloud and evolutionary computing, computer engineering and applications, knowledge management and applications, communication technology and applications.

Applications of Machine Learning in Big-Data Analytics and Cloud Computing
Applications of Machine Learning in Big-Data Analytics and Cloud Computing

Author: Subhendu Kumar Pani

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 346

ISBN-13: 1000793559

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Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Data Intensive Computing Applications for Big Data
Data Intensive Computing Applications for Big Data

Author: M. Mittal

Publisher: IOS Press

Published: 2018-01-31

Total Pages: 618

ISBN-13: 1614998140

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The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Applications of Data Mining in Computer Security
Applications of Data Mining in Computer Security

Author: Daniel Barbará

Publisher: Springer Science & Business Media

Published: 2002-05-31

Total Pages: 286

ISBN-13: 9781402070549

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Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security. Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.

Information and Beyond: Part I
Information and Beyond: Part I

Author: Eli Cohen.

Publisher: Informing Science

Published:

Total Pages: 445

ISBN-13: 1932886036

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Research papers on Collaborative Work / Working Together / Teams, Control, Audit, and Security, Curriculum Issues, Decision Making / Business Intelligence (DM/BI), Distance Education & e-Learning, Doctoral Studies, Economic Aspects, Education / Training, Educational Assessment & Evaluation, Ethical, and Social, & Cultural Issues

Information, Computer and Application Engineering
Information, Computer and Application Engineering

Author: Hsiang-Chuan Liu

Publisher: CRC Press

Published: 2018-06-12

Total Pages: 1146

ISBN-13: 0429785526

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This proceedings volume brings together peer-reviewed papers presented at the International Conference on Information Technology and Computer Application Engineering, held 10-11 December 2014, in Hong Kong, China. Specific topics under consideration include Computational Intelligence, Computer Science and its Applications, Intelligent Information Processing and Knowledge Engineering, Intelligent Networks and Instruments, Multimedia Signal Processing and Analysis, Intelligent Computer-Aided Design Systems and other related topics. This book provides readers a state-of-the-art survey of recent innovations and research worldwide in Information Technology and Computer Application Engineering, in so-doing furthering the development and growth of these research fields, strengthening international academic cooperation and communication, and promoting the fruitful exchange of research ideas. This volume will be of interest to professionals and academics alike, serving as a broad overview of the latest advances in the dynamic field of Information Technology and Computer Application Engineering.

Bio-Inspired Computing for Information Retrieval Applications
Bio-Inspired Computing for Information Retrieval Applications

Author: Acharjya, D.P.

Publisher: IGI Global

Published: 2017-02-14

Total Pages: 411

ISBN-13: 1522523766

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The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary studies on data processing, swarm-based clustering, and evolutionary computation, this publication is an ideal reference source for researchers, academics, professionals, students, and practitioners.

Computing Attitude and Affect in Text: Theory and Applications
Computing Attitude and Affect in Text: Theory and Applications

Author: James G. Shanahan

Publisher: Springer Science & Business Media

Published: 2006-01-17

Total Pages: 346

ISBN-13: 1402041020

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Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the “factual” aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author’s reports from reports of other people’s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers’ aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an “NLP”-complete problem.

Data-Intensive Computing
Data-Intensive Computing

Author: Ian Gorton

Publisher: Cambridge University Press

Published: 2012-10-29

Total Pages: 299

ISBN-13: 1139788507

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The world is awash with digital data from social networks, blogs, business, science and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud and describe example applications in bioinformatics and cybersecurity that illustrate these principles in practice.