Literature Based Discovery Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Literature Based Discovery book. This book definitely worth reading, it is an incredibly well-written.
Literature-based Discovery by Peter Bruza,Marc Weeber Pdf
This is the first coherent book on literature-based discovery (LBD). LBD is an inherently multi-disciplinary enterprise. The aim of this volume is to plant a flag in the ground and inspire new researchers to the LBD challenge.
Literature-based Discovery by Peter Bruza,Marc Weeber Pdf
This is the first coherent book on literature-based discovery (LBD). LBD is an inherently multi-disciplinary enterprise. The aim of this volume is to plant a flag in the ground and inspire new researchers to the LBD challenge.
Trends and Applications in Knowledge Discovery and Data Mining by Wei Lu,Kenny Q. Zhu Pdf
This book constitutes the thoroughly refereed post-workshop proceedings of the workshops that were held in conjunction with the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, in Singapore, Singapore, in May 2020. The 17 revised full papers presented were carefully reviewed and selected from a total of 50 submissions. The five workshops were as follows: · First International Workshop on Literature-Based Discovery (LBD 2020) · Workshop on Data Science for Fake News (DSFN 2020) · Learning Data Representation for Clustering (LDRC 2020) · Ninth Workshop on Biologically Inspired Techniques for Data Mining (BDM · 2020) · First Pacific Asia Workshop on Game Intelligence & Informatics (GII 2020)
Biological Knowledge Discovery Handbook by Mourad Elloumi,Albert Y. Zomaya Pdf
The first comprehensive overview of preprocessing, mining,and postprocessing of biological data Molecular biology is undergoing exponential growth in both thevolume and complexity of biological data—and knowledgediscovery offers the capacity to automate complex search and dataanalysis tasks. This book presents a vast overview of the mostrecent developments on techniques and approaches in the field ofbiological knowledge discovery and data mining (KDD)—providingin-depth fundamental and technical field information on the mostimportant topics encountered. Written by top experts, Biological Knowledge DiscoveryHandbook: Preprocessing, Mining, and Postprocessing of BiologicalData covers the three main phases of knowledge discovery (datapreprocessing, data processing—also known as datamining—and data postprocessing) and analyzes both verificationsystems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological DataMining Combining sound theory with practical applications in molecularbiology, Biological Knowledge Discovery Handbook is idealfor courses in bioinformatics and biological KDD as well as forpractitioners and professional researchers in computer science,life science, and mathematics.
Bisociative Knowledge Discovery by Michael R. Berthold Pdf
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Computational Discovery of Scientific Knowledge by Saso Dzeroski,Ljupco Todorovski Pdf
This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.
This volume details step-by-step instructions on biomedical literature mining protocols. Chapters guide readers through various topics such as, disease comorbidity, literature-based discovery, protocols to combine literature mining, machine learning for predicting biomedical discoveries, and uncovering unknown public knowledge by combining two pieces of information from different sets of PubMed articles. Additional chapters discuss the importance of data science to understand outbreaks such as COVID-19. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Biomedical Text Mining aims to be a useful practical guide to researches to help further their studies.
Secondary Research Methods in the Built Environment by Emmanuel Manu,Julius Akotia Pdf
The first book to cover secondary research methods in built environment topics Incorporates chapters dealing with qualitative secondary analysis, systematic review technique, legal analysis, bibliometric and scientometric analysis Global market across a variety of courses/subjects including: construction management, construction project management, quantity surveying, construction law and dispute resolution, real estate and property management, building services engineering, architecture and civil engineering
Interdisciplinary Knowledge Organization by Rick Szostak,Claudio Gnoli,María López-Huertas Pdf
This book proposes a novel approach to classification, discusses its myriad advantages, and outlines how such an approach to classification can best be pursued. It encourages a collaborative effort toward the detailed development of such a classification. This book is motivated by the increased importance of interdisciplinary scholarship in the academy, and the widely perceived shortcomings of existing knowledge organization schemes in serving interdisciplinary scholarship. It is designed for scholars of classification research, knowledge organization, the digital environment, and interdisciplinarity itself. The approach recommended blends a general classification with domain-specific classification practices. The book reaches a set of very strong conclusions: -Existing classification systems serve interdisciplinary research and teaching poorly. -A novel approach to classification, grounded in the phenomena studied rather than disciplines, would serve interdisciplinary scholarship much better. It would also have advantages for disciplinary scholarship. The productivity of scholarship would thus be increased. -This novel approach is entirely feasible. Various concerns that might be raised can each be addressed. The broad outlines of what a new classification would look like are developed. -This new approach might serve as a complement to or a substitute for existing classification systems. -Domain analysis can and should be employed in the pursuit of a general classification. This will be particularly important with respect to interdisciplinary domains. -Though the impetus for this novel approach comes from interdisciplinarity, it is also better suited to the needs of the Semantic Web, and a digital environment more generally. Though the primary focus of the book is on classification systems, most chapters also address how the analysis could be extended to thesauri and ontologies. The possibility of a universal thesaurus is explored. The classification proposed has many of the advantages sought in ontologies for the Semantic Web. The book is therefore of interest to scholars working in these areas as well.
"Turning Points: The Nature of Creativity" discusses theories and methods focusing on a critical concept of intellectual turning points in the context of critical thinking, scientific discovery, and problem solving in general. This book introduces a novel analytical and experimental system that provides not only new ways for retrospective studies of scientific change but also for characterizing transformative potentials of prospective scientific contributions. The book is intended for scientists and researchers in the fields of information science and computer science. Dr. Chaomei Chen is an Associate Professor at the College of Information Science and Technology, Drexel University, USA.
Mining Text Data by Charu C. Aggarwal,ChengXiang Zhai Pdf
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
Machine Learning for Health Informatics by Andreas Holzinger Pdf
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Artificial Intelligence in Science Challenges, Opportunities and the Future of Research by OECD Pdf
The rapid advances of artificial intelligence (AI) in recent years have led to numerous creative applications in science. Accelerating the productivity of science could be the most economically and socially valuable of all the uses of AI.
Natural Language Processing and Information Systems by Elisabeth Métais,Farid Meziane,Mohamad Saraee,Vijayan Sugumaran,Sunil Vadera Pdf
This book constitutes the refereed proceedings of the 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, held in Salford, UK, in June 2016. The 17 full papers, 22 short papers, and 13 poster papers presented were carefully reviewed and selected from 83 submissions. The papers cover the following topics: theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP.