Alexander Mehler – författare

For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A  tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book''s major goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks.

This volume is the first to present a self-contained, comprehensive overview of information-theoretic models of complex networks with an emphasis on applications. As such, it marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines and can serve as a valuable resource for a diverse audience of advanced students and professional scientists. While it is primarily intended as a reference for research, the book could also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.

This book addresses the topic of online information for everyday personal and professional use by students, graduates, and young professionals. It focuses on the development of the job-related use of online information by young professionals in their practical phases of education (traineeship/practical year) in the domains of law, teaching, and medicine. The research conducted in this context investigates the general and domain-specific use of online resources in educational contexts and examines the effectiveness of an innovative digital training approach in enhancing skills required for the competent use of online information. For this purpose, the presented research uses a yet unprecedented approach of data triangulation, in which self-rated data, digitally and in vivo assessed response process data and expert ratings are integrated into a theoretically founded assessment framework and are examined from various interdisciplinary perspectives with different analysis methods.Overall, this work addresses key research questions related to the use of online information in practical tasks as well as to the impact of digital training. It provides in-depth multidisciplinary analyses of multimodal processes and performance data, allowing implications equally relevant for practitioners, policymakers, and researchers in the field of education. 

The Handbook of Technical Communication brings together a variety of topics which range from the role of technical media in human communication to the linguistic, multimodal enhancement of present-day technologies. It covers the area of computer-mediated text, voice and multimedia communication as well as of technical documentation. In doing so, the handbook takes professional and private communication into account.Special emphasis is put on technical communication by means of web 2.0 technologies and its standardization in system development. In summary, the handbook deals with theoretical issues of technical communication and its practical impact on the development and usage of text and speech technologies.

This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects the most recent achievements with respect to the automatic build-up of large lexical resources. It addresses researchers that already perform text mining, and those who want to enrich their battery of methods. Selected articles can be used to support graduate-level teaching.

The book is suitable for all readers that completed undergraduate studies of computational linguistics, quantitativelinguistics, computer science and computational humanities. It assumes basic knowledge of computer science and corpus processing as well as of statistics.

The significance of natural language texts as the prime information structure for the management and dissemination of knowledge is - as the rise of the web shows - still increasing. Making relevant texts available in different contexts is of primary importance for efficient task completion in academic and industrial settings. Meeting this demand requires automatic form and content based processing of texts, which enables to reconstruct or even to explore the dynamic relationship of language system, text event and context type. The rise of new application areas, disciplines and methods (e.g. text and web mining) testify to the importance of this task. Moreover, the growing area of new media demands the further development of methods of text analysis with respect to their computational linguistic, information theoretical, and mathematical underpinning. This book contributes to this task. It collects contributions of authors from a multidisciplinary area who focus on the topic of automatic text analysis from several (i.e. linguistic, mathematical, and information theoretical) perspectives. It describes methodological as well as methodical foundations and collects approaches in the field of text and corpus linguistics. In this sense, it contributes to the computational linguistic and information theoretical grounding of automatic text analysis.

Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.

The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities. This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statistical models of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information science. It may also be of interest for the upcoming area of systems biology with which the chapters collected here share the view on systems from the point of view of network analysis.

The volume “Genres on the Web” has been designed for a wide audience, from the expert to the novice. It is a required book for scholars, researchers and students who want to become acquainted with the latest theoretical, empirical and computational advances in the expanding field of web genre research. The study of web genre is an overarching and interdisciplinary novel area of research that spans from corpus linguistics, computational linguistics, NLP, and text-technology, to web mining, webometrics, social network analysis and information studies. This book gives readers a thorough grounding in the latest research on web genres and emerging document types.

The book covers a wide range of web-genre focused subjects, such as: • The identification of the sources of web genres • Automatic web genre identification • The presentation of structure-oriented models • Empirical case studies

One of the driving forces behind genre research is the idea ofa genre-sensitive information system, which incorporates genre cues complementing the current keyword-based search and retrieval applications.