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This book focuses on information geometry manifolds of structured data/information and their advanced applications featuring new and fruitful interactions between several branches of science: information science, mathematics and physics. It addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds, relational and discrete metric spaces, computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing. The book collects the most important contributions to the conference GSI’2017 – Geometric Science of Information.
Formalization plays an important role in semantics. Doing semantics and following the literature requires considerable technical sophistica tion and acquaintance with quite advanced mathematical techniques and structures. But semantics isn't mathematics. These techniques and structures are tools that help us build semantic theories. Our real aim is to understand semantic phenomena and we need the technique to make our understanding of these phenomena precise. The problems in semantics are most often too hard and slippery, to completely trust our informal understanding of them. This should not be taken as an attack on informal reasoning in semantics. On the contrary, in my view, very often the essential insight in a diagnosis of what is going on in a certain semantic phenomenon takes place at the informal level. It is very easy, however, to be misled into thinking that a certain informal insight provides a satisfying analysis of a certain problem; it will often turn out that there is a fundamental unclarity about what the informal insight actually is. Formalization helps to sharpen those insights and put them to the test.
This book provides linguists with a clear, critical, and comprehensive overview of theoretical and experimental work on information structure. Leading researchers survey the main theories of information structure in syntax, phonology, and semantics as well as perspectives from psycholinguistics and other relevant fields. Following the editors' introduction the book is divided into four parts. The first, on theories of and theoretical perspectives on information structure, includes chapters on topic, prosody, and implicature. Part 2 covers a range of current issues in the field, including focus, quantification, and sign languages, while Part 3 is concerned with experimental approaches to information structure, including processes involved in its acquisition and comprehension. The final part contains a series of linguistic case studies drawn from a wide variety of the world's language families. This volume will be the standard guide to current work in information structure and a major point of departure for future research.
With its theme, "Our Information, Always and Forever," Part I of this book covers the basics of personal information management (PIM) including six essential activities of PIM and six (different) ways in which information can be personal to us. Part I then goes on to explore key issues that arise in the "great migration" of our information onto the Web and into a myriad of mobile devices. Part 2 provides a more focused look at technologies for managing information that promise to profoundly alter our practices of PIM and, through these practices, the way we lead our lives. Part 2 is in five chapters: - Chapter 5. Technologies of Input and Output. Technologies in support of gesture, touch, voice, and even eye movements combine to support a more natural user interface (NUI). Technologies of output include glasses and "watch" watches. Output will also increasingly be animated with options to "zoom". - Chapter 6. Technologies to Save Our Information. We can opt for "life logs" to record our experiences with increasing fidelity. What will we use these logs for? And what isn’t recorded that should be? - Chapter 7. Technologies to Search Our Information. The potential for personalized search is enormous and mostly yet to be realized. Persistent searches, situated in our information landscape, will allow us to maintain a diversity of projects and areas of interest without a need to continually switch from one to another to handle incoming information. - Chapter 8. Technologies to Structure Our Information. Structure is key if we are to keep, find, and make effective use of our information. But how best to structure? And how best to share structured information between the applications we use, with other people, and also with ourselves over time? What lessons can we draw from the failures and successes in web-based efforts to share structure? - Chapter 9. PIM Transformed and Transforming: Stories from the Past, Present and Future. Part 2 concludes with a comparison between Licklider’s world of information in 1957 and our own world of information today. And then we consider what the world of information is likely to look like in 2057. Licklider estimated that he spent 85% of his "thinking time" in activities that were clerical and mechanical and might (someday) be delegated to the computer. What percentage of our own time is spent with the clerical and mechanical? What about in 2057?
This book covers those aspects of a computer science course normally referred to as 'information structures' or 'data structures'. It covers the techniques of information hiding, specification, data type realization, and tuning. It is written to be read as well as studied and includes a wealth of examples in Pascal, all motivated and described. Exercises at the end of the book are designed to highlight the major concepts, and to encourage the student to use a disciplined approach to program construction. Its underlying theme is 'data abstraction' and this theme binds the book into a complete and cohesive college course, aimed directly at undergraduate computer science students in their first and second years of study.
If you’re a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering—data structures and algorithms—in a way that’s clearer, more concise, and more engaging than other materials. By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You’ll explore the important classes in the Java collections framework (JCF), how they’re implemented, and how they’re expected to perform. Each chapter presents hands-on exercises supported by test code online. Use data structures such as lists and maps, and understand how they work Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree Analyze code to predict how fast it will run and how much memory it will require Write classes that implement the Map interface, using a hash table and binary search tree Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.
In many fields of science and practice large amounts of data and informationare collected for analyzing and visualizing latent structures as orderings or classifications for example. This volume presents refereed and revised versions of 52 papers selected from the contributions of the 16th AnnualConference of the "German Classification Society". The papers are organized in three major sections on Data Analysis and Classification (1), InformationRetrieval, Knowledge Processing and Software (2), Applications and Special Topics (3). Moreover, the papers were grouped and ordered within the major sections. So, in the first section we find papers on Classification Methods, Fuzzy Classification, Multidimensional Scaling, Discriminant Analysis and Conceptual Analysis. The second section contains papers on Neural Networks and Computational Linguisticsin addition to the mentioned fields. An essential part of the third section attends to Sequence Data and Tree Reconstruction as well as Data Analysis and Informatics in Medicine. As special topics the volume presents applications in Thesauri, Archaeology, Musical Science and Psychometrics.
No detailed description available for "Syntactic Structures".
This series consists of collected volumes and monographs about specific issues dealing with interfaces among the subcomponents of linguistic structure: phonology-morphology, phonology-syntax, syntax-semantics, syntax-morphology, and syntax-lexicon. Recent linguistic research has recognized that the subcomponents of grammar interact in non-trivial ways. What is currently under debate is the actual range of such interactions and their most appropriate representation in grammar, and this is precisely the focus of this series. Specifically, it provides a general overview of various topics by examining them through the interaction of grammatical components. The books function as a state-of- the-art report of research.