Welcome to the Advanced Workshop on Content Computing 2004. The focus of this workshop was "Content Computing". It emphasized research areas that facilitate efficient, appropriate dissemination of content to users with the necessary access rights. We use the word "content" instead of "information" or "data" because we want to cover not only raw data but also presentation quality. The fast growth of the Internet has already made it the key infrastructure for information dissemination,education,business and entertainment. While the client-server model has been the most widely adopted paradigm for the WWW, the desire to provide more value-added services in the delivery layer has led to the concept of an active network, where content-driven, intelligent computation will be performed to provide quality-of-service for content presentation and best-?t client demand. These value-added services typically aim to enhance information security, provide pervasive Internet access, and improve application robustness, system/network performance, knowledge extraction,etc. They are realized by incorporating sophisticated mechanisms at the delivery layer,which is transparent to the content providers and Web surfers. Consequently, the notion of "Content Computing" has emerged. Content computing is a new paradigm for coordinating distributed systems and intelligent networks, based on a peer-to-peer model and with value-added processing of the application-specific contents at the - livery layer. This paradigm is especially useful to pervasive lightweight client devices such as mobile and portable end-user terminals with a wide variation of hardware/software configurations. This year, the workshop was held in Zhenjiang, Jiangsu, China. We received 194 high-quality papers from 11 regions, namely PR China, Korea, Singapore, Japan, United States, Canada, Australia, Germany, Taiwan, Italy, and Hong Kong. Totally, 62 papers were accepted and presented in the workshop.

Faced with a full-blown crisis, a growing number of journalists are engaging in seemingly unjournalistic practices such as creating and maintaining databases, handling algorithms, or designing online applications. “Data journalists” claim that these approaches help the profession demonstrate greater objectivity and fulfill its democratic mission. In their view, computational methods enable journalists to better inform their readers, more closely monitor those in power, and offer deeper analysis. In Computing the News, Sylvain Parasie examines how data journalists and news organizations have navigated the tensions between traditional journalistic values and new technologies. He traces the history of journalistic hopes for computing technology and contextualizes the surge of data journalism in the twenty-first century. By importing computational techniques and ways of knowing new to journalism, news organizations have come to depend on a broader array of human and nonhuman actors. Parasie draws on extensive fieldwork in the United States and France, including interviews with journalists and data scientists as well as a behind-the-scenes look at several acclaimed projects in both countries. Ultimately, he argues, fulfilling the promise of data journalism requires the renewal of journalistic standards and ethics. Offering an in-depth analysis of how computing has become part of the daily practices of journalists, this book proposes ways for journalism to evolve in order to serve democratic societies.

An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to

Are women really kicking butt in computer science? National statistics show little progress in the participation of women in computing; this in spite of numerous studies, reports and recommendations on the topic. Some might say the reasons for the situation remain a mystery. However, at Carnegie Mellon University we do not believe that the situation is either so mysterious or such an intractable problem. Indeed, women are kicking butt in computer science in some cultures and environments. This book tells the Carnegie Mellon story, a positive story of how one school developed a culture and environment in which both women and men could thrive and be successful in computer science.

This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system.

Natural computing brings together nature and computing to develop new computational tools for problem solving; to synthesize natural patterns and behaviors in computers; and to potentially design novel types of computers. Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications presents a wide-ranging survey of novel techniqu

This textbook raises thought-provoking questions regarding our rapidly-evolving computing technologies, highlighting the need for a strong ethical framework in our computer science education. Ethics in Computing offers a concise introduction to this topic, distilled from the more expansive Ethical and Social Issues in the Information Age. Features: introduces the philosophical framework for analyzing computer ethics; describes the impact of computer technology on issues of security, privacy and anonymity; examines intellectual property rights in the context of computing; discusses such issues as the digital divide, employee monitoring in the workplace, and health risks; reviews the history of computer crimes and the threat of cyberbullying; provides coverage of the ethics of AI, virtualization technologies, virtual reality, and the Internet; considers the social, moral and ethical challenges arising from social networks and mobile communication technologies; includes discussion questions and exercises.

An accessible and rigorous textbook for introducing undergraduates to computer science theory What Can Be Computed? is a uniquely accessible yet rigorous introduction to the most profound ideas at the heart of computer science. Crafted specifically for undergraduates who are studying the subject for the first time, and requiring minimal prerequisites, the book focuses on the essential fundamentals of computer science theory and features a practical approach that uses real computer programs (Python and Java) and encourages active experimentation. It is also ideal for self-study and reference. The book covers the standard topics in the theory of computation, including Turing machines and finite automata, universal computation, nondeterminism, Turing and Karp reductions, undecidability, time-complexity classes such as P and NP, and NP-completeness, including the Cook-Levin Theorem. But the book also provides a broader view of computer science and its historical development, with discussions of Turing's original 1936 computing machines, the connections between undecidability and Gödel's incompleteness theorem, and Karp's famous set of twenty-one NP-complete problems. Throughout, the book recasts traditional computer science concepts by considering how computer programs are used to solve real problems. Standard theorems are stated and proven with full mathematical rigor, but motivation and understanding are enhanced by considering concrete implementations. The book's examples and other content allow readers to view demonstrations of—and to experiment with—a wide selection of the topics it covers. The result is an ideal text for an introduction to the theory of computation. An accessible and rigorous introduction to the essential fundamentals of computer science theory, written specifically for undergraduates taking introduction to the theory of computation Features a practical, interactive approach using real computer programs (Python in the text, with forthcoming Java alternatives online) to enhance motivation and understanding Gives equal emphasis to computability and complexity Includes special topics that demonstrate the profound nature of key ideas in the theory of computation Lecture slides and Python programs are available at whatcanbecomputed.com

What Is Computer Science Ontology An ontology is a representation, formal naming, and specification of the categories, qualities, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. In the field of information science, an ontology covers all of these elements. To put it another way, an ontology is a method of establishing a group of concepts and categories that are representative of a topic area in order to demonstrate how the characteristics of that subject area are related to one another. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Ontology (computer science) Chapter 2: Cyc Chapter 3: Knowledge representation and reasoning Chapter 4: Semantic Web Chapter 5: Web Ontology Language Chapter 6: Description logic Chapter 7: Modeling language Chapter 8: Upper ontology Chapter 9: Ontology language Chapter 10: Ontology engineering (II) Answering the public top questions about computer science ontology. (III) Real world examples for the usage of computer science ontology in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of computer science ontology' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of computer science ontology.