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Author: New York University
Publisher: Springer Science & Business Media
ISBN: 1475740468
Category : Computers
Languages : en
Pages : 195
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Book Description
This monograph is a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. Some topics covered are algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection. Included are self-contained descriptions of wavelets, fast Fourier transforms, and sketches as they apply to time-series analysis. Detailed applications are built on a solid scientific basis.
Author: New York University
Publisher: Springer Science & Business Media
ISBN: 1475740468
Category : Computers
Languages : en
Pages : 195
Get Book Here
Book Description
This monograph is a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. Some topics covered are algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection. Included are self-contained descriptions of wavelets, fast Fourier transforms, and sketches as they apply to time-series analysis. Detailed applications are built on a solid scientific basis.
Author: Pierre Marquis
Publisher: Springer Nature
ISBN: 3030061701
Category : Technology & Engineering
Languages : en
Pages : 584
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Book Description
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.
Author: Zohra Bellahsene
Publisher: Springer Science & Business Media
ISBN: 3642165184
Category : Computers
Languages : en
Pages : 326
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Book Description
Requiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation. The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field. With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.
Author: Dennis Elliott Shasha
Publisher: Springer Science & Business Media
ISBN: 9780387008578
Category : Computers
Languages : en
Pages : 210
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Book Description
Time-series data—data arriving in time order, or a data stream—can be found in fields such as physics, finance, music, networking, and medical instrumentation. Designing fast, scalable algorithms for analyzing single or multiple time series can lead to scientific discoveries, medical diagnoses, and perhaps profits. High Performance Discovery in Time Series presents rapid-discovery techniques for finding portions of time series with many events (i.e., gamma-ray scatterings) and finding closely related time series (i.e., highly correlated price and return histories, or musical melodies). A typical time-series technique may compute a "consensus" time series—from a collection of time series—to use regression analysis for predicting future time points. By contrast, this book aims at efficient discovery in time series, rather than prediction, and its novelty lies in its algorithmic contributions and its simple, practical algorithms and case studies. It presumes familiarity with only basic calculus and some linear algebra. Topics and Features: *Presents efficient algorithms for discovering unusual bursts of activity in large time-series databases * Describes the mathematics and algorithms for finding correlation relationships between thousands or millions of time series across fixed or moving windows *Demonstrates strong, relevant applications built on a solid scientific basis *Outlines how readers can adapt the techniques for their own needs and goals *Describes algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection *Offers self-contained descriptions of wavelets, fast Fourier transforms, and sketches as they apply to time-series analysis This new monograph provides a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. It offers essential coverage of the topic for computer scientists, physicists, medical researchers, financial mathematicians, musicologists, and researchers and professionals who must analyze massive time series. In addition, it can serve as an ideal text/reference for graduate students in many data-rich disciplines.
Author: Siau, Keng
Publisher: IGI Global
ISBN: 1609605225
Category : Computers
Languages : en
Pages : 418
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Book Description
Information system design and development is of interest and importance to researchers and practitioners, as advances in this discipline impact a number of other related fields and help to guide future research. Theoretical and Practical Advances in Information Systems Development: Emerging Trends and Approaches contains fundamental concepts, emerging theories, and practical applications in database management, systems analysis and design, and software engineering. Contributions present critical findings in information resources management that inform and advance the field.
Author: Charu C. Aggarwal
Publisher: Springer
ISBN: 3319078216
Category : Computers
Languages : en
Pages : 480
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Book Description
This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.
Author: Xiaofeng Meng
Publisher: Springer Science & Business Media
ISBN: 3642382762
Category : Computers
Languages : en
Pages : 244
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Book Description
Applications, 2nd Edition focuses on moving object management, from the location management perspective to determining how constantly changing locations affect the traditional database and data mining technology. The book specifically describes the topics of moving objects modeling and location tracking, indexing and querying, clustering, location uncertainty, traffic-aware navigation and privacy issues, as well as the application to intelligent transportation systems. Through the book, the readers will be made familiar with the cutting-edge technologies in moving object management that can be effectively applied in LBS and transportation contexts. The second edition of this book significantly expands the coverage of the latest research on location privacy, traffic-aware navigation and uncertainty. The book has also been reorganized, with nearly all chapters rewritten, and several new chapters have been added to address the latest topics on moving objects management. Xiaofeng Meng is a professor at the School of Information, Renmin University of China; Zhiming Ding is a professor at the Institute of Software, Chinese Academy of Sciences (ISCAS); Jiajie Xu is an assistant professor at the ISCAS.
Author: Stefano Spaccapietra
Publisher: Springer Science & Business Media
ISBN: 3540242082
Category : Computers
Languages : en
Pages : 233
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Book Description
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Author: Nauman Chaudhry
Publisher: Springer Science & Business Media
ISBN: 0387252290
Category : Computers
Languages : en
Pages : 179
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Book Description
Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.
Author: Taniar, David
Publisher: IGI Global
ISBN: 1599042738
Category : Computers
Languages : en
Pages : 350
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Book Description
Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery process, data models, structures, and design serve as answers and solutions to these emerging challenges.
