Bücher veröffentlicht von Springer US

Mining the World Wide Web: An Information Search Approach explores the concepts and techniques of Web mining, a promising and rapidly growing field of computer science research. Web mining is a multidisciplinary field, drawing on such areas as artificial intelligence, databases, data mining, data warehousing, data visualization, information retrieval, machine learning, markup languages, pattern recognition, statistics, and Web technology. Mining the World Wide Web presents the Web mining material from an information search perspective, focusing on issues relating to the efficiency, feasibility, scalability and usability of searching techniques for Web mining. Mining the World Wide Web is designed for researchers and developers of Web information systems and also serves as an excellent supplemental reference to advanced level courses in data mining, databases and information retrieval.

Dr. Heinonen reviews and critically evaluates the scientific literature on the biological role of inorganic pyrophosphate (PPi ) published from 1940 to the end of 1999. He describes and classifies all known biochemical reactions that produce Ppi; describes and evaluates all published methods used in biological Ppi; and compiles and critically evaluates information on the concentration of PPi (with the conclusion that, contrary to common belief, PPi exists throughout the living world in rather high concentrations). Many reactions in which PPi is used as a biochemical energy source instead of ATP have been described in recent decades, especially in bacteria, protists, and plants. These reactions are evaluated from the bioenergetic and regulatory points of view. Also considered is the possible role of PPi as a source of biochemical energy in the primitive phases of life, before ATP. Data is presented on the regulatory role of PPi in living systems, such as activities of enzymes, fidelity of syntheses of macromolecules, and proliferation of cells. PPi may also regulate the formation and dissolution of bone as well as pathologic calcification of soft tissues and the formation of urinary stones. The formation of calcium pyrophosphate dihydrate crystals in the extracellular fluids of joints cause the disease called pseudogout. Biological Role of Inorganic Pyrophosphate book is a unique and invaluable source of references (about 1120) and summarized data for professionals who study or plan to study the role of PPi in living systems. Many different branches of science (biochemistry, microbiology, bioenergetics, plant physiology, parasitology, evolution, orthopedics, rheumatology) have involvement with PPi. This book sums up available knowledge in one place and will help scientists cross disciplinary boundaries.

Recent Advances in RSA Cryptography surveys the most important achievements of the last 22 years of research in RSA cryptography. Special emphasis is laid on the description and analysis of proposed attacks against the RSA cryptosystem. The first chapters introduce the necessary background information on number theory, complexity and public key cryptography. Subsequent chapters review factorization algorithms and specific properties that make RSA attractive for cryptographers. Most recent attacks against RSA are discussed in the third part of the book (among them attacks against low-exponent RSA, Hastad's broadcast attack, and Franklin-Reiter attacks). Finally, the last chapter reviews the use of the RSA function in signature schemes. Recent Advances in RSA Cryptography is of interest to graduate level students and researchers who will gain an insight into current research topics in the field and an overview of recent results in a unified way. Recent Advances in RSA Cryptography is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.

North American Parasitic Zoonoses provides a concise and useful review of essential information about parasitic zoonotic diseases. Key topics include: -Etiology/ Natural History: Account of taxonomy, morphology as necessary for identification, and life cycles; -Epidemiology: Global prevalence and prevalence in North America among various demographic groups in both human and non-human hosts. Consideration of primary risk factors associated with transmission; - Pathogenesis. - Diagnostic tests; - Treatment and control measures: Current drug(s) of choice, contraindications, and procedures utilized in the treatment of human infection. Consideration of practical steps to be taken in the prevention of transmission; - Recent Advances and Contemporary Challenges: A discussion of the most exciting contemporary areas of research concerning each disease with recommendations for future avenues of study. North American Parasitic Zoonoses, volume six of "e;World Class Parasites"e;, is written for researchers, students, veterinarians, physicians and scholars who enjoy reading research that has a major impact on human health, or agricultural productivity, and against which we have no satisfactory defense. It is intended to supplement more formal texts that cover taxonomy, life cycles, morphology, vector distribution, symptoms and treatment. It integrates vector, pathogen and host biology and celebrates the diversity of approach that comprises modern parasitological research.

An authoritative reference to the whole area of source coding algorithms, Compression and Coding Algorithms will be a primary resource for both researchers and software engineers. The book also will be interest for people in broader area of design and analysis of algorithms and data structure. Practitioners, especially those who work in the software development and independent consulting industries creating compression software or other applications systems, in which compression plays a part, will benefit from techniques that are described. Compression and Coding Algorithms describes in detail the coding mechanisms that are available for use in data compression systems. The well known Huffman coding technique is one mechanism, but there have been many others developed over the past few decades, and this book describes, explains and assesses them. People undertaking research of software development in the areas of compression and coding algorithms will find this book an indispensable reference. In particular, the careful and detailed description of algorithms and their implementation, plus accompanying pseudo-code that can be readily implemented on computer, make this book a definitive reference in an area currently without one.The detailed pseudo-code presentation of over thirty algorithms, and careful explanation of examples, make this book approachable and authoritative. Compression and throughput results are presented where appropriate, and serve as a validation of the assessments and recommendation made in the text. The combination of implementation detail, thoughtful discussions, and careful presentation means that this book will occupy a pivotal role in this area for many years. In-depth coverage of the crucial areas of minimum-redundancy coding, arithmetic coding, adaptive coding make Compression and Coding Algorithms unique in its field.

Text Classification, or the task of automatically assigning semantic categories to natural language text, has become one of the key methods for organizing online information. Since hand-coding classification rules is costly or even impractical, most modern approaches employ machine learning techniques to automatically learn text classifiers from examples. However, none of these conventional approaches combines good prediction performance, theoretical understanding, and efficient training algorithms.Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications.Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.Learning To Classify Text Using Support Vector Machines is designed as a reference for researchers and practitioners, and is suitable as a secondary text for graduate-level students in Computer Science within Machine Learning and Language Technology.

Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system. It is an excellent reference for researchers interested in adaptive behavior and machine learning from a cognitive science perspective as well as those who are interested in combining evolutionary learning mechanisms for learning and optimization tasks.

Software architectures have gained wide popularity in the last decade. They generally play a fundamental role in coping with the inherent difficulties of the development of large-scale and complex software systems. Component-oriented and aspect-oriented programming enables software engineers to implement complex applications from a set of pre-defined components. Software Architectures and Component Technology collects excellent chapters on software architectures and component technologies from well-known authors, who not only explain the advantages, but also present the shortcomings of the current approaches while introducing novel solutions to overcome the shortcomings. The unique features of this book are: evaluates the current architecture design methods and component composition techniques and explains their shortcomings; presents three practical architecture design methods in detail; gives four industrial architecture design examples; presents conceptual models for distributed message-based architectures; explains techniques for refining architectures into components; presents the recent developments in component and aspect-oriented techniques; explains the status of research on Piccola, Hyper/J(R), Pluggable Composite Adapters and Composition Filters. Software Architectures and Component Technology is a suitable text for graduate level students in computer science and engineering, and as a reference for researchers and practitioners in industry.