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This book constitutes the proceedings of the 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, which took place in Padua, Italy, in September 2022. The 18 full papers, 27 short papers and 15 accelerating innovation papers included in these proceedings were carefully reviewed and selected from 107 submissions. They focus on digital libraries and associated technical, practical, and social issues.
This book constitutes the proceedings of the 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, held in September 2021. Due to COVID-10 pandemic the conference was held virtually. The 10 full papers, 3 short papers and 13 other papers presented were carefully reviewed and selected from 53 submissions. TPDL 2021 attempts to facilitate establishing connections and convergences between diverse research communities such as Digital Humanities, Information Sciences and others that could benefit from ecosystems offered by digital libraries and repositories. This edition of TPDL was held under the general theme of “Linking Theory and Practice”. The papers are organized in topical sections as follows: Document and Text Analysis; Data Repositories and Archives; Linked Data and Open Data; User Interfaces and Experience.
All aspects of digital libraries are in scope for JCDL This includes but is not limited to digital information discovery, collection, management, retrieval, (re )use, distribution, and preservation Models and standards for digital data description are also in scope, as well as institutional systems, platforms, and services to facilitate the broad spectrum around digital (research) data management Digital libraries further entail the many aspects of digital preservation, from storage concepts to file formats to access methods It covers many media types, the entire information life cycle, and provides research areas for computer scientists, information scientists, librarians, archivists, historians, journalists in academia, industry, and nonprofits
This open access book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on the event by assessing how articles portray the persons involved in the event. In contrast to prior automated approaches, the identified frames are more meaningful and substantially present in person-oriented news coverage. The book is structured in seven chapters: Chapter 1 presents a few of the severe problems caused by slanted news coverage and identifies the research gap that motivated the research described in this thesis. Chapter 2 discusses manual analysis concepts and exemplary studies from the social sciences and automated approaches, mostly from computer science and computational linguistics, to analyze and reveal media bias. This way, it identifies the strengths and weaknesses of current approaches for identifying and revealing media bias. Chapter 3 discusses the solution design space to address the identified research gap and introduces person-oriented framing analysis (PFA), a new approach to identify substantial frames and to reveal slanted news coverage. Chapters 4 and 5 detail target concept analysis and frame identification, the first and second component of PFA. Chapter 5 also introduces the first large-scale dataset and a novel model for target-dependent sentiment classification (TSC) in the news domain. Eventually, Chapter 6 introduces Newsalyze, a prototype system to reveal biases to non-expert news consumers by using the PFA approach. In the end, Chapter 7 summarizes the thesis and discusses the strengths and weaknesses of the thesis to derive ideas for future research on media bias. This book mainly targets researchers and graduate students from computer science, computational linguistics, political science, and further social sciences who want to get an overview of the relevant state of the art in the other related disciplines and understand and tackle the issue of bias from a more effective, interdisciplinary viewpoint.
Zusammenfassung: This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens.
This book constitutes the refereed proceedings of the 27th International Conference on Linking Theory and Practice of Digital Libraries, TPDL 2023, held in Zadar, Croatia, during September 26–29, 2023. The 13 full papers and 17 short papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: Applications and digital library systems; data citation and citation analysis; discovering science, monitoring and publishing science; knowledge creation; Human-Computer Interaction; digital humanities; and digital cultural heritage.