Entity-Oriented Search

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

From text mining to knowledge mining: An integrated framework of concept extraction and categorization for domain ontology

Organizations are struggling with the challenges coming from the regulatory, social and economic environment which are complex and changing continuously. They cause increase demand for the management of organizational knowledge, like how to provide employees, the necessary job-specific knowledge in right time and in right format. Employees have to update their knowledge, improve their competencies continuously. Knowledge repositories have key roles from knowledge management aspects, because they contain primarily the organizations’ intellectual assets (it is explicit knowledge) while employees have tacit knowledge, which is difficult to extract and codify. Business processes are also important from the management of organizational knowledge aspects, they have explicit and tacit knowledge elements as well. One of the key questions is how to handle this hidden knowledge in order to improve the organizational knowledge especially employees' knowledge by providing the most appropriate learning and/or training materials and how can we ensure that the knowledge in business processes are the same as in knowledge repositories and employees' head. These are the major themes in this thesis

Design and Instantiation of an Interactive Multidimensional Ontology for Game Design Elements – a Design and Behavioral Approach

While games and play are commonly perceived as leisure tools, focus on the strategic implementation of isolated gameful elements outside of games has risen in recent years under the term gamification. Given their ease of implementation and impact in competitive games, a small set of game design elements, namely points, badges, and leaderboards, initially dominated research and practice. However, these elements reflect only a small group of components that game designers use to achieve positive outcomes in their systems. Current research has shifted towards focusing on the game design process instead of the isolated implementation of single elements under the term gameful design. But the problem of a tendency toward a monocultural selection of prominent design elements persists in-game and gameful design, preventing the method from reaching its full potential. This dissertation addresses this problem by designing and developing a digital, interactive game design element ontology that scholars and practitioners can use to make more informed and inspired decisions in creating gameful solutions to their problems. The first part of this work is concerned with the collation and development of the digital ontology. First, two datasets were collated from game design and gamification literature (game design elements and playing motivations). Next, four explorative studies were conducted to add user-relevant metadata and connect their items into an ontological structure. The first two studies use card sorting to assess game theory frameworks regarding their suitability as foundational categories for the game design element dataset and to gain an overview of different viewpoints from which categorizations can be derived. The second set of studies builds on an explorative method of matching dataset entries via their descriptive keywords to arrive at a connected graph. The first of these studies connects items of the playing motivations dataset with themselves, while the second connects them with an additional dataset of human needs. The first part closes with the documentation of the design and development of the tool Kubun, reporting on the outcome of its evaluation via iterative expert interviews and a field study. The results suggest that the tool serves its preset goals of affording intuitive browsing for dedicated searches and serendipitous findings. While the first part of this work reports on the top-down development process of the ontology and related navigation tool, the second part presents an in-depth research of specific learning-oriented game design elements to complement the overall research goal through a complementary bottom-up approach. Therein, two studies on learning-oriented game design elements are reported regarding their effect on performance, long-term learning outcome, and knowledge transfer. The studies are conducted with a game dedicated to teaching correct waste sorting. The first study focuses on a reward-based game design element in terms of its motivatory effect on perfect play. The second study evaluates two learning-enhancing game design elements, repeat, and look-up, in terms of their contribution to a long-term learning outcome. The comprehensive insights gained through the in-depth research manifest in the design of a module dedicated to reporting research outcomes in the ontology. The dissertation concludes with a discussion on the studies’ varying limitations and an outlook on pathways for future research

Narrative in the Age of the Genome

Shortlisted for the 2021 BSLS Book Prize Genomic technologies have had a profound impact on understandings of what it means to be human and our links to the world we inhabit, and on practices of inhabiting the world. This open access book considers this impact across a range of literary forms, cultural practices, and political imaginaries, and argues that new descriptions of biological value introduced through practices of genomic sequencing from the late 1970s registered a broader crisis of narrative form. Examining a wide range of texts by Doris Lessing, Samuel Delany, Boris and Arkady Strugatsky, Kir Bulychev, Kazuo Ishiguro, Saidiya Hartman, Yaa Gyasi, Svetlana Alexievich, and Jeff VanderMeer, Narrative in the Age of the Genome casts new light on the intersections of genomics with politics of racism, sexuality, labour and gender, neoliberal economics and environmental crisis. The eBook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by The Wellcome Trus

Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

The study of low-dimensional, noisy manifolds embedded in a higher dimensional space has been extremely useful in many applications, from the chemical analysis of multi-phase flows to simulations of galactic mergers. Building a probabilistic model of the manifolds has helped in describing their essential properties and how they vary in space. However, when the manifold is evolving through time, a joint spatio-temporal modelling is needed, in order to fully comprehend its nature. We propose a first-order Markovian process that propagates the spatial probabilistic model of a manifold at fixed time, to its adjacent temporal stages. The proposed methodology is demonstrated using a particle simulation of an interacting dwarf galaxy to describe the evolution of a cavity generated by a Supernov

What People Leave Behind

This open access book focuses on a particular but significant topic in the social sciences: the concepts of “footprint” and “trace”. It associates these concepts with hotly debated topics such as surveillance capitalism and knowledge society. The editors and authors discuss the concept footprints and traces as unintended by-products of other (differently focused and oriented) actions that remain empirically imprinted in virtual and real spaces. The volume therefore opens new scenarios for social theory and applied social research in asking what the stakes, risks and potential of this approach are. It systematically raises and addresses these questions within a consistent framework, bringing together a heterogeneous group of international social scientists. Given the multifaceted objectives involved in exploring footprints and traces, the volume discusses heuristic aspects and ethical dimensions, scientific analyses and political considerations, empirical perspectives and theoretical foundations. At the same time, it brings together perspectives from cultural analysis and social theory, communication and Internet studies, big-data informed research and computational social science. This innovative volume is of interest to a broad interdisciplinary readership: sociologists, communication researchers, Internet scholars, anthropologists, cognitive and behavioral scientists, historians, and epistemologists, among others

Approaches to Automatic Text Structuring

Structured text helps readers to better understand the content of documents. In classic newspaper texts or books, some structure already exists. In the Web 2.0, the amount of textual data, especially user-generated data, has increased dramatically. As a result, there exists a large amount of textual data which lacks structure, thus making it more difficult to understand. In this thesis, we will explore techniques for automatic text structuring to help readers to fulfill their information needs. Useful techniques for automatic text structuring are keyphrase identification, table-of-contents generation, and link identification. We improve state of the art results for approaches to text structuring on several benchmark datasets. In addition, we present new representative datasets for users’ everyday tasks. We evaluate the quality of text structuring approaches with regard to these scenarios and discover that the quality of approaches highly depends on the dataset on which they are applied. In the first chapter of this thesis, we establish the theoretical foundations regarding text structuring. We describe our findings from a user survey regarding web usage from which we derive three typical scenarios of Internet users. We then proceed to the three main contributions of this thesis. We evaluate approaches to keyphrase identification both by extracting and assigning keyphrases for English and German datasets. We find that unsupervised keyphrase extraction yields stable results, but for datasets with predefined keyphrases, additional filtering of keyphrases and assignment approaches yields even higher results. We present a de- compounding extension, which further improves results for datasets with shorter texts. We construct hierarchical table-of-contents of documents for three English datasets and discover that the results for hierarchy identification are sufficient for an automatic system, but for segment title generation, user interaction based on suggestions is required. We investigate approaches to link identification, including the subtasks of identifying the mention (anchor) of the link and linking the mention to an entity (target). Approaches that make use of the Wikipedia link structure perform best, as long as there is sufficient training data available. For identifying links to sense inventories other than Wikipedia, approaches that do not make use of the link structure outperform the approaches using existing links. We further analyze the effect of senses on computing similarities. In contrast to entity linking, where most entities can be discriminated by their name, we consider cases where multiple entities with the same name exist. We discover that similarity de- pends on the selected sense inventory. To foster future evaluation of natural language processing components for text structuring, we present two prototypes of text structuring systems, which integrate techniques for automatic text structuring in a wiki setting and in an e-learning setting with eBooks

ICS Materials. Towards a re-Interpretation of material qualities through interactive, connected, and smart materials.

The domain of materials for design is changing under the influence of an increased technological advancement, miniaturization and democratization. Materials are becoming connected, augmented, computational, interactive, active, responsive, and dynamic. These are ICS Materials, an acronym that stands for Interactive, Connected and Smart. While labs around the world are experimenting with these new materials, there is the need to reflect on their potentials and impact on design. This paper is a first step in this direction: to interpret and describe the qualities of ICS materials, considering their experiential pattern, their expressive sensorial dimension, and their aesthetic of interaction. Through case studies, we analyse and classify these emerging ICS Materials and identified common characteristics, and challenges, e.g. the ability to change over time or their programmability by the designers and users. On that basis, we argue there is the need to reframe and redesign existing models to describe ICS materials, making their qualities emerge

What People Leave Behind

This open access book focuses on a particular but significant topic in the social sciences: the concepts of “footprint” and “trace”. It associates these concepts with hotly debated topics such as surveillance capitalism and knowledge society. The editors and authors discuss the concept footprints and traces as unintended by-products of other (differently focused and oriented) actions that remain empirically imprinted in virtual and real spaces. The volume therefore opens new scenarios for social theory and applied social research in asking what the stakes, risks and potential of this approach are. It systematically raises and addresses these questions within a consistent framework, bringing together a heterogeneous group of international social scientists. Given the multifaceted objectives involved in exploring footprints and traces, the volume discusses heuristic aspects and ethical dimensions, scientific analyses and political considerations, empirical perspectives and theoretical foundations. At the same time, it brings together perspectives from cultural analysis and social theory, communication and Internet studies, big-data informed research and computational social science. This innovative volume is of interest to a broad interdisciplinary readership: sociologists, communication researchers, Internet scholars, anthropologists, cognitive and behavioral scientists, historians, and epistemologists, among others

Semantic Systems. The Power of AI and Knowledge Graphs

This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies