springer international publishing springer international publishing sep 2010 (14 résultats)

Taschenbuch. Etat : Neu. Neuware -Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of the relationship between the source and the target. Such a target instance should correctly represent information from the source instance under the constraints imposed by the target schema, and it should allow one to evaluate queries on the target instance in a way that is semantically consistent with the source data. Data exchange is an old problem that re-emerged as an active research topic recently, due to the increased need for exchange of data in various formats, often in e-business applications. In this lecture, we give an overview of the basic concepts of data exchange in both relational and XML contexts. We give examples of data exchange problems, and we introduce the main tasks that need to addressed. We then discuss relational data exchange, concentrating on issues such as relational schema mappings, materializing target instances (including canonical solutions and cores), query answering, and query rewriting. After that, we discuss metadata management, i.e., handling schema mappings themselves. We pay particular attention to operations on schema mappings, such as composition and inverse. Finally, we describe both data exchange and metadata management in the context of XML. We use mappings based on transforming tree patterns, and we show that they lead to a host of new problems that did not arise in the relational case, but they need to be addressed for XML. These include consistency issues for mappings and schemas, as well as imposing tighter restrictions on mappings and queries to achieve tractable query answering in data exchange. Table of Contents: Overview / Relational Mappings and Data Exchange / Metadata Management / XML Mappings and Data ExchangeSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes data cubes and their elements, such as dimensions, facts, and measures and their representation in a relational setting; it includes architecture-related concepts; and it includes the querying of multidimensional databases. The book also covers advanced multidimensional concepts that are considered to be particularly important. This coverage includes advanced dimension-related concepts such as slowly changing dimensions, degenerate and junk dimensions, outriggers, parent-child hierarchies, and unbalanced, non-covering, and non-strict hierarchies. The book offers a principled overview of key implementation techniques that are particularly important to multidimensional databases, including materialized views, bitmap indices, join indices, and star join processing. The book ends with a chapter that presents the literature on which the book is based and offers further readings for those readers who wish to engage in more in-depth study of specific aspects of the book's subject. Table of Contents: Introduction / Fundamental Concepts / Advanced Concepts / Implementation Issues / Further ReadingsSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel.This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information.Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media MiningSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 140 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -Database replication is widely used for fault-tolerance, scalability and performance. The failure of one database replica does not stop the system from working as available replicas can take over the tasks of the failed replica. Scalability can be achieved by distributing the load across all replicas, and adding new replicas should the load increase. Finally, database replication can provide fast local access, even if clients are geographically distributed clients, if data copies are located close to clients. Despite its advantages, replication is not a straightforward technique to apply, and there are many hurdles to overcome. At the forefront is replica control: assuring that data copies remain consistent when updates occur. There exist many alternatives in regard to where updates can occur and when changes are propagated to data copies, how changes are applied, where the replication tool is located, etc. A particular challenge is to combine replica control with transaction management as it requires several operations to be treated as a single logical unit, and it provides atomicity, consistency, isolation and durability across the replicated system. The book provides a categorization of replica control mechanisms, presents several replica and concurrency control mechanisms in detail, and discusses many of the issues that arise when such solutions need to be implemented within or on top of relational database systems. Furthermore, the book presents the tasks that are needed to build a fault-tolerant replication solution, provides an overview of load-balancing strategies that allow load to be equally distributed across all replicas, and introduces the concept of self-provisioning that allows the replicated system to dynamically decide on the number of replicas that are needed to handle the current load. As performance evaluation is a crucial aspect when developing a replication tool, the book presents an analytical model of the scalability potential of various replication solution. For readers that are only interested in getting a good overview of the challenges of database replication and the general mechanisms of how to implement replication solutions, we recommend to read Chapters 1 to 4. For readers that want to get a more complete picture and a discussion of advanced issues, we further recommend the Chapters 5, 8, 9 and 10. Finally, Chapters 6 and 7 are of interest for those who want get familiar with thorough algorithm design and correctness reasoning. Table of Contents: Overview / 1-Copy-Equivalence and Consistency / Basic Protocols / Replication Architecture / The Scalability of Replication / Eager Replication and 1-Copy-Serializability / 1-Copy-Snapshot Isolation / Lazy Replication / Self-Configuration and Elasticity / Other Aspects of ReplicationSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 156 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -Face detection, because of its vast array of applications, is one of the most active research areas in computer vision. In this book, we review various approaches to face detection developed in the past decade, with more emphasis on boosting-based learning algorithms. We then present a series of algorithms that are empowered by the statistical view of boosting and the concept of multiple instance learning. We start by describing a boosting learning framework that is capable to handle billions of training examples. It differs from traditional bootstrapping schemes in that no intermediate thresholds need to be set during training, yet the total number of negative examples used for feature selection remains constant and focused (on the poor performing ones). A multiple instance pruning scheme is then adopted to set the intermediate thresholds after boosting learning. This algorithm generates detectors that are both fast and accurate. We then present two multiple instance learning schemesfor face detection, multiple instance learning boosting (MILBoost) and winner-take-all multiple category boosting (WTA-McBoost). MILBoost addresses the uncertainty in accurately pinpointing the location of the object being detected, while WTA-McBoost addresses the uncertainty in determining the most appropriate subcategory label for multiview object detection. Both schemes can resolve the ambiguity of the labeling process and reduce outliers during training, which leads to improved detector performances. In many applications, a detector trained with generic data sets may not perform optimally in a new environment. We propose detection adaption, which is a promising solution for this problem. We present an adaptation scheme based on the Taylor expansion of the boosting learning objective function, and we propose to store the second order statistics of the generic training data for future adaptation. We show that with a small amount of labeled data in the new environment, the detector'sperformance can be greatly improved. We also present two interesting applications where boosting learning was applied successfully. The first application is face verification for filtering and ranking image/video search results on celebrities. We present boosted multi-task learning (MTL), yet another boosting learning algorithm that extends MILBoost with a graphical model. Since the available number of training images for each celebrity may be limited, learning individual classifiers for each person may cause overfitting. MTL jointly learns classifiers for multiple people by sharing a few boosting classifiers in order to avoid overfitting. The second application addresses the need of speaker detection in conference rooms. The goal is to find who is speaking, given a microphone array and a panoramic video of the room. We show that by combining audio and visual features in a boosting framework, we can determine the speaker's position very accurately. Finally, we offer our thoughts on future directions for face detection. Table of Contents: A Brief Survey of the Face Detection Literature / Cascade-based Real-Time Face Detection / Multiple Instance Learning for Face Detection / Detector Adaptation / Other Applications / Conclusions and Future WorkSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 144 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -Transactional memory (TM) is an appealing paradigm for concurrent programming on shared memory architectures. With a TM, threads of an application communicate, and synchronize their actions, via in-memory transactions. Each transaction can perform any number of operations on shared data, and then either commit or abort. When the transaction commits, the effects of all its operations become immediately visible to other transactions; when it aborts, however, those effects are entirely discarded. Transactions are atomic: programmers get the illusion that every transaction executes all its operations instantaneously, at some single and unique point in time. Yet, a TM runs transactions concurrently to leverage the parallelism offered by modern processors. The aim of this book is to provide theoretical foundations for transactional memory. This includes defining a model of a TM, as well as answering precisely when a TM implementation is correct, what kind of properties it can ensure, what are the power and limitations of a TM, and what inherent trade-offs are involved in designing a TM algorithm. While the focus of this book is on the fundamental principles, its goal is to capture the common intuition behind the semantics of TMs and the properties of existing TM implementations. Table of Contents: Introduction / Shared Memory Systems / Transactional Memory: A Primer / TM Correctness Issues / Implementing a TM / Further Reading / Opacity / Proving Opacity: An Example / Opacity vs. Atomicity / Further Reading / The Liveness of a TM / Lock-Based TMs / Obstruction-Free TMs / General Liveness of TMs / Further Reading / ConclusionsSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of the relationship between the source and the target. Such a target instance should correctly represent information from the source instance under the constraints imposed by the target schema, and it should allow one to evaluate queries on the target instance in a way that is semantically consistent with the source data. Data exchange is an old problem that re-emerged as an active research topic recently, due to the increased need for exchange of data in various formats, often in e-business applications. In this lecture, we give an overview of the basic concepts of data exchange in both relational and XML contexts. We give examples of data exchange problems, and we introduce the main tasks that need to addressed. We then discuss relational data exchange, concentrating on issues such as relational schema mappings, materializing target instances (including canonical solutions and cores), query answering, and query rewriting. After that, we discuss metadata management, i.e., handling schema mappings themselves. We pay particular attention to operations on schema mappings, such as composition and inverse. Finally, we describe both data exchange and metadata management in the context of XML. We use mappings based on transforming tree patterns, and we show that they lead to a host of new problems that did not arise in the relational case, but they need to be addressed for XML. These include consistency issues for mappings and schemas, as well as imposing tighter restrictions on mappings and queries to achieve tractable query answering in data exchange. Table of Contents: Overview / Relational Mappings and Data Exchange / Metadata Management / XML Mappings and Data Exchange 112 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes data cubes and their elements, such as dimensions, facts, and measures and their representation in a relational setting; it includes architecture-related concepts; and it includes the querying of multidimensional databases. The book also covers advanced multidimensional concepts that are considered to be particularly important. This coverage includes advanced dimension-related concepts such as slowly changing dimensions, degenerate and junk dimensions, outriggers, parent-child hierarchies, and unbalanced, non-covering, and non-strict hierarchies. The book offers a principled overview of key implementation techniques that are particularly important to multidimensional databases, including materialized views, bitmap indices, join indices, and star join processing. The book ends with a chapter that presents the literature on which the book is based and offers further readings for those readers who wish to engage in more in-depth study of specific aspects of the book's subject. Table of Contents: Introduction / Fundamental Concepts / Advanced Concepts / Implementation Issues / Further Readings 112 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Database replication is widely used for fault-tolerance, scalability and performance. The failure of one database replica does not stop the system from working as available replicas can take over the tasks of the failed replica. Scalability can be achieved by distributing the load across all replicas, and adding new replicas should the load increase. Finally, database replication can provide fast local access, even if clients are geographically distributed clients, if data copies are located close to clients. Despite its advantages, replication is not a straightforward technique to apply, and there are many hurdles to overcome. At the forefront is replica control: assuring that data copies remain consistent when updates occur. There exist many alternatives in regard to where updates can occur and when changes are propagated to data copies, how changes are applied, where the replication tool is located, etc. A particular challenge is to combine replica control with transaction management as it requires several operations to be treated as a single logical unit, and it provides atomicity, consistency, isolation and durability across the replicated system. The book provides a categorization of replica control mechanisms, presents several replica and concurrency control mechanisms in detail, and discusses many of the issues that arise when such solutions need to be implemented within or on top of relational database systems. Furthermore, the book presents the tasks that are needed to build a fault-tolerant replication solution, provides an overview of load-balancing strategies that allow load to be equally distributed across all replicas, and introduces the concept of self-provisioning that allows the replicated system to dynamically decide on the number of replicas that are needed to handle the current load. As performance evaluation is a crucial aspect when developing a replication tool, the book presents an analytical model of the scalability potential of various replication solution. For readers that are only interested in getting a good overview of the challenges of database replication and the general mechanisms of how to implement replication solutions, we recommend to read Chapters 1 to 4. For readers that want to get a more complete picture and a discussion of advanced issues, we further recommend the Chapters 5, 8, 9 and 10. Finally, Chapters 6 and 7 are of interest for those who want get familiar with thorough algorithm design and correctness reasoning. Table of Contents: Overview / 1-Copy-Equivalence and Consistency / Basic Protocols / Replication Architecture / The Scalability of Replication / Eager Replication and 1-Copy-Serializability / 1-Copy-Snapshot Isolation / Lazy Replication / Self-Configuration and Elasticity / Other Aspects of Replication 156 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel.This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information.Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining 140 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochasticutility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions 212 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Face detection, because of its vast array of applications, is one of the most active research areas in computer vision. In this book, we review various approaches to face detection developed in the past decade, with more emphasis on boosting-based learning algorithms. We then present a series of algorithms that are empowered by the statistical view of boosting and the concept of multiple instance learning. We start by describing a boosting learning framework that is capable to handle billions of training examples. It differs from traditional bootstrapping schemes in that no intermediate thresholds need to be set during training, yet the total number of negative examples used for feature selection remains constant and focused (on the poor performing ones). A multiple instance pruning scheme is then adopted to set the intermediate thresholds after boosting learning. This algorithm generates detectors that are both fast and accurate. We then present two multiple instance learning schemes for face detection, multiple instance learning boosting (MILBoost) and winner-take-all multiple category boosting (WTA-McBoost). MILBoost addresses the uncertainty in accurately pinpointing the location of the object being detected, while WTA-McBoost addresses the uncertainty in determining the most appropriate subcategory label for multiview object detection. Both schemes can resolve the ambiguity of the labeling process and reduce outliers during training, which leads to improved detector performances. In many applications, a detector trained with generic data sets may not perform optimally in a new environment. We propose detection adaption, which is a promising solution for this problem. We present an adaptation scheme based on the Taylor expansion of the boosting learning objective function, and we propose to store the second order statistics of the generic training data for future adaptation. We show that with a small amount of labeled data in the new environment, the detector's performance can be greatly improved. We also present two interesting applications where boosting learning was applied successfully. The first application is face verification for filtering and ranking image/video search results on celebrities. We present boosted multi-task learning (MTL), yet another boosting learning algorithm that extends MILBoost with a graphical model. Since the available number of training images for each celebrity may be limited, learning individual classifiers for each person may cause overfitting. MTL jointly learns classifiers for multiple people by sharing a few boosting classifiers in order to avoid overfitting. The second application addresses the need of speaker detection in conference rooms. The goal is to find who is speaking, given a microphone array and a panoramic video of the room. We show that by combining audio and visual features in a boosting framework, we can determine the speaker's position very accurately. Finally, we offer our thoughts on future directions for face detection. Table of Contents: A Brief Survey of the Face Detection Literature / Cascade-based Real-Time Face Detection / Multiple Instance Learning for Face Detection / Detector Adaptation / Other Applications / Conclusions and Future Work 144 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochasticutility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / ConclusionsSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 212 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Transactional memory (TM) is an appealing paradigm for concurrent programming on shared memory architectures. With a TM, threads of an application communicate, and synchronize their actions, via in-memory transactions. Each transaction can perform any number of operations on shared data, and then either commit or abort. When the transaction commits, the effects of all its operations become immediately visible to other transactions; when it aborts, however, those effects are entirely discarded. Transactions are atomic: programmers get the illusion that every transaction executes all its operations instantaneously, at some single and unique point in time. Yet, a TM runs transactions concurrently to leverage the parallelism offered by modern processors. The aim of this book is to provide theoretical foundations for transactional memory. This includes defining a model of a TM, as well as answering precisely when a TM implementation is correct, what kind of properties it can ensure, what are the power and limitations of a TM, and what inherent trade-offs are involved in designing a TM algorithm. While the focus of this book is on the fundamental principles, its goal is to capture the common intuition behind the semantics of TMs and the properties of existing TM implementations. Table of Contents: Introduction / Shared Memory Systems / Transactional Memory: A Primer / TM Correctness Issues / Implementing a TM / Further Reading / Opacity / Proving Opacity: An Example / Opacity vs. Atomicity / Further Reading / The Liveness of a TM / Lock-Based TMs / Obstruction-Free TMs / General Liveness of TMs / Further Reading / Conclusions 196 pp. Englisch.