Download or read book Privacy and Identity Management written by Michael Friedewald and published by Springer Nature. This book was released on 2021-03-31 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.* The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives. *The summer school was held virtually.

Download or read book Innovative Document Summarization Techniques Revolutionizing Knowledge Understanding written by Fiori, Alessandro and published by IGI Global. This book was released on 2014-01-31 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The prevalence of digital documentation presents some pressing concerns for efficient information retrieval in the modern age. Readers want to be able to access the information they desire without having to search through a mountain of unrelated data, so algorithms and methods for effectively seeking out pertinent information are of critical importance. Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding evaluates some of the existing approaches to information retrieval and summarization of digital documents, as well as current research and future developments. This book serves as a sounding board for students, educators, researchers, and practitioners of information technology, advancing the ongoing discussion of communication in the digital age.

Download or read book Knowledge Discovery Knowledge Engineering and Knowledge Management written by Ana Fred and published by Springer. This book was released on 2015-10-27 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 6th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2014, held in Rome, Italy, in October 2014. The 37 full papers presented were carefully reviewed and selected from 287 submissions. The papers are organized in topical sections on knowledge discovery and information retrieval; knowledge engineering and ontology development; knowledge management and information sharing.

Download or read book Deep Learning for Natural Language Processing written by Mihai Surdeanu and published by Cambridge University Press. This book was released on 2024-01-31 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.

Download or read book Computational Processing of the Portuguese Language written by Helena Caseli and published by Springer. This book was released on 2012-03-09 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 8th International Workshop on Computational Processing of the Portuguese Language, PROPOR 2012, held in Coimbra, Portugal in April 2012. The 24 revised full papers and 23 revised short papers presented were carefully reviewed and selected from 86 submissions. These papers cover the areas related to phonology, morphology and POS-Tagging, acquisition, language resources, linguistic description, syntax and parsing, semantics, opinion analysis, natural language processing applications, speech production and phonetics, speech resources, speech processing and applications.

Download or read book Empirical Methods in Natural Language Generation written by Emiel Krahmer and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

Download or read book Financial Decision Making Using Computational Intelligence written by Michael Doumpos and published by Springer Science & Business Media. This book was released on 2012-07-23 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.

Download or read book Proceedings of International Conference on Frontiers in Computing and Systems written by Subhadip Basu and published by Springer Nature. This book was released on 2022-06-27 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the 2nd International Conference on Frontiers in Computing and Systems (COMSYS 2021), organized by Department of Electronics and Communication Engineering and Department of Information Technology, North-Eastern Hill University, Shillong, Meghalaya, India held during September 29–October 1, 2021. The book presents the latest research and results in various fields of machine learning, computational intelligence, VLSI, networks and systems, computational biology, and security, making it a rich source of reference material for academia and industry alike.

Download or read book From Opinion Mining to Financial Argument Mining written by Chung-Chi Chen and published by Springer Nature. This book was released on 2021 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.

Download or read book Entity Oriented Search written by Krisztian Balog and published by Springer. This book was released on 2018-10-02 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms.

Download or read book Dialogues with Social Robots written by Kristiina Jokinen and published by Springer. This book was released on 2016-12-23 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores novel aspects of social robotics, spoken dialogue systems, human-robot interaction, spoken language understanding, multimodal communication, and system evaluation. It offers a variety of perspectives on and solutions to the most important questions about advanced techniques for social robots and chat systems. Chapters by leading researchers address key research and development topics in the field of spoken dialogue systems, focusing in particular on three special themes: dialogue state tracking, evaluation of human-robot dialogue in social robotics, and socio-cognitive language processing. The book offers a valuable resource for researchers and practitioners in both academia and industry whose work involves advanced interaction technology and who are seeking an up-to-date overview of the key topics. It also provides supplementary educational material for courses on state-of-the-art dialogue system technologies, social robotics, and related research fields.

Download or read book From Extractive to Abstractive Summarization A Journey written by Parth Mehta and published by Springer. This book was released on 2019-08-13 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent advances in text summarization, identifies remaining gaps and challenges, and proposes ways to overcome them. It begins with one of the most frequently discussed topics in text summarization – ‘sentence extraction’ –, examines the effectiveness of current techniques in domain-specific text summarization, and proposes several improvements. In turn, the book describes the application of summarization in the legal and scientific domains, describing two new corpora that consist of more than 100 thousand court judgments and more than 20 thousand scientific articles, with the corresponding manually written summaries. The availability of these large-scale corpora opens up the possibility of using the now popular data-driven approaches based on deep learning. The book then highlights the effectiveness of neural sentence extraction approaches, which perform just as well as rule-based approaches, but without the need for any manual annotation. As a next step, multiple techniques for creating ensembles of sentence extractors – which deliver better and more robust summaries – are proposed. In closing, the book presents a neural network-based model for sentence compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.

Download or read book Biomedical Informatics written by Edward H. Shortliffe and published by Springer Science & Business Media. This book was released on 2013-12-02 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies.

Download or read book Workload Measures written by Valerie Jane Gawron and published by CRC Press. This book was released on 2019-01-04 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was developed to help researchers and practitioners select measures to be used in the evaluation of human/machine systems. The book includes definitions of human workload and a review of measures. Each measure is described, along with its strengths and limitations, data requirements, threshold values, and sources of further information. To make this reference easier to use, extensive author and subject indices are provided. Features Offers readily accessible information on workload measures Presents general description of the measure Covers data collection, reduction, and analysis requirements Details the strengths and limitations or restrictions of each measure, including proprietary rights or restrictions Provides validity and reliability data as available

Download or read book Ubiquitous Learning Environments and Technologies written by Kinshuk and published by Springer. This book was released on 2014-09-10 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the design and architecture of ubiquitous learning environments, associated technologies, various learning scenarios supported by these environments, and different contexts that arise in environments where the seamless immersion of formal and informal activities and interactions has the potential to contribute to the learning process. With particular focus on adaptivity for individual learners, the book explores the diminishing boundaries of formal and informal learning, and the potential of location-aware context-sensitive approaches that are emerging as successors to the Web 2.0 paradigm.

Download or read book Opinion Analysis For Online Reviews written by Yuming Lin and published by World Scientific. This book was released on 2016-06-02 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the problem of combination explosion encountered, a greedy algorithm is devised to select the base classifiers.

Download or read book Deep Learning Techniques Applied to Affective Computing written by Zhen Cui and published by Frontiers Media SA. This book was released on 2023-06-14 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affective computing refers to computing that relates to, arises from, or influences emotions. The goal of affective computing is to bridge the gap between humans and machines and ultimately endow machines with emotional intelligence for improving natural human-machine interaction. In the context of human-robot interaction (HRI), it is hoped that robots can be endowed with human-like capabilities of observation, interpretation, and emotional expression. The research on affective computing has recently achieved extensive progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing concentrates on estimating human emotions through different forms of signals such as speech, face, text, EEG, fMRI, and many others. In neuroscience, the neural mechanisms of emotion are explored by combining neuroscience with the psychological study of personality, emotion, and mood. In psychology and philosophy, emotion typically includes a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. The multi-disciplinary features of understanding “emotion” result in the fact that inferring the emotion of humans is definitely difficult. As a result, a multi-disciplinary approach is required to facilitate the development of affective computing. One of the challenging problems in affective computing is the affective gap, i.e., the inconsistency between the extracted feature representations and subjective emotions. To bridge the affective gap, various hand-crafted features have been widely employed to characterize subjective emotions. However, these hand-crafted features are usually low-level, and they may hence not be discriminative enough to depict subjective emotions. To address this issue, the recently-emerged deep learning (also called deep neural networks) techniques provide a possible solution. Due to the used multi-layer network structure, deep learning techniques are capable of learning high-level contributing features from a large dataset and have exhibited excellent performance in multiple application domains such as computer vision, signal processing, natural language processing, human-computer interaction, and so on. The goal of this Research Topic is to gather novel contributions on deep learning techniques applied to affective computing across the diverse fields of psychology, machine learning, neuroscience, education, behavior, sociology, and computer science to converge with those active in other research areas, such as speech emotion recognition, facial expression recognition, Electroencephalogram (EEG) based emotion estimation, human physiological signal (heart rate) estimation, affective human-robot interaction, multimodal affective computing, etc. We welcome researchers to contribute their original papers as well as review articles to provide works regarding the neural approach from computation to affective computing systems. This Research Topic aims to bring together research including, but not limited to: • Deep learning architectures and algorithms for affective computing tasks such as emotion recognition from speech, face, text, EEG, fMRI, and many others. • Explainability of deep Learning algorithms for affective computing. • Multi-task learning techniques for emotion, personality and depression detection, etc. • Novel datasets for affective computing • Applications of affective computing in robots, such as emotion-aware human-robot interaction and social robots, etc.