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See below for a selection of the latest books from Information retrieval category. Presented with a red border are the Information retrieval books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Information retrieval books and those from many more genres to read that will keep you inspired and entertained. And it's all free!
This book constitutes the refereed proceedings of the Second International Conference on HCI in Games, HCI-Games 2020, held in July 2020 as part of HCI International 2020 in Copenhagen, Denmark.* HCII 2020 received a total of 6326 submissions, of which 1439 papers and 238 posters were accepted for publication after a careful reviewing process. The 38 papers presented in this volume are organized in topical sections named: designing games and gamified interactions; user engagement and game impact; and serious games. *The conference was held virtually due to the COVID-19 pandemic.
This book constitutes the proceedings of the 20th International Conference on Web Engineering, ICWE 2020, which was planned to take place in Helsinki, Finland, during June 9-12, 2020. Due to the corona pandemic the conference changed to a virtual format. The total of 24 full and 10 short contributions presented in this volume were carefully reviewed and selected from 78 submissions. The book also contains 4 PhD and 7 demo papers. The papers were organized in topical sections named: User interface technologies; performance of Web technologies; machine learning; testing of Web applications; emotion detection; location-aware applications; sentiment analysis; open data; liquid Web applications; Web-based learning; PhD symposium; demos and posters.
This book constitutes the refereed proceedings of the Second International Symposium on Benchmarking, Measuring, and Optimization, Bench 2019, held in Denver, CO, USA, in November 2019. The 20 full papers and 11 short papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections named: Best Paper Session; AI Challenges on Cambircon using AIBenc; AI Challenges on RISC-V using AIBench; AI Challenges on X86 using AIBench; AI Challenges on 3D Face Recognition using AIBench; Benchmark; AI and Edge; Big Data; Datacenter; Performance Analysis; Scientific Computing.
This book constitutes the refereed proceedings of the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, held in Grenoble, France, in June 2020.* The 33 full papers presented in this volume were carefully reviewed and selected from 185 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: distributed applications; AI and big data in IS; process mining and analysis; requirements and modeling; and information systems engineering. Abstracts on the CAiSE 2020 tutorials can be found in the back matter of the volume. *The conference was held virtually due to the COVID-19 pandemic.
This edited book adopts a cognitive perspective to provide breadth and depth to state-of-the-art research related to understanding, analyzing, predicting and improving one of the most prominent and important classes of behavior of modern humans, information search. It is timely as the broader research area of cognitive computing and cognitive technology have recently attracted much attention, and there has been a surge in interest to develop systems and technology that are more compatible with human cognitive abilities. Divided into three interlocking sections, the first introduces the foundational concepts of information search from a cognitive computing perspective to highlight the research questions and approaches that are shared among the contributing authors. Relevant concepts from psychology, information and computing sciences are addressed. The second section discusses methods and tools that are used to understand and predict information search behavior and how the cognitive perspective can provide unique insights into the complexities of the behavior in various contexts. The final part highlights a number of areas of applications of which education and training, collaboration and conversational search interfaces are important ones. Understanding and Improving Information Search - A Cognitive Approach includes contributions from cognitive psychologists, information and computing scientists around the globe, including researchers from Europe (France, Netherlands, Germany), the US, and Asia (India, Japan), providing their unique but coherent perspectives to the core issues and questions most relevant to our current understanding of information search behavior and improving information search.
This book constitutes the refereed proceedings of the 17th International Semantic Web Conference, ESWC 2020, held in Heraklion, Crete, Greece.* The 39 revised full papers presented were carefully reviewed and selected from 166 submissions. The papers were submitted to three tracks: the research track, the resource track and the in-use track. These tracks showcase research and development activities, services and applications, and innovative research outcomes making their way into industry. The research track caters for both long standing and emerging research topics in the form of the following subtracks: ontologies and reasoning; natural language processing and information retrieval; semantic data management and data infrastructures; social and human aspects of the Semantic Web; machine learning; distribution and decentralization; science of science; security, privacy, licensing and trust; knowledge graphs; and integration, services and APIs. *The conference was held virtually due to the COVID-19 pandemic. Chapter 'Piveau: A Large-scale Oopen Data Management Platform based on Semantic Web Technologies' is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self-study, it aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. Principles of Data Mining includes descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift. The expanded fourth edition gives a detailed description of a feed-forward neural network with backpropagation and shows how it can be used for classification.
This book constitutes the thoroughly refereed proceedings of the international workshops associated with the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, which was planned to take place in Grenoble, France, during June 8-12, 2020. Due to the Coronavirus pandemic the conference was held virtually. The workshops included in this book are: KET4DF, The Second International Workshop on Key Enabling Technologies for Digital Factories ISESL, The First International Workshop on Information Systems Engineering for Smarter Life The total of 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The book also contains one invited talk.
This volume constitutes the refereed and revised post-conference proceedings of the 4th IFIP TC 5 DCITDRR International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2019, in Kyiv, Ukraine, in October 2019. The 17 full papers and 2 short papers presented were carefully reviewed and selected from 53 submissions. The papers focus on various aspects and challenges of coping with disaster risk reduction. The main topics include areas such as natural disasters, big data, cloud computing, Internet of Things, mobile computing, emergency management, disaster information processing, and disaster risk assessment and management.
This book gathers recent research work on emerging Artificial Intelligence (AI) methods for processing and storing data generated by cloud-based Internet of Things (IoT) infrastructures. Major topics covered include the analysis and development of AI-powered mechanisms in future IoT applications and architectures. Further, the book addresses new technological developments, current research trends, and industry needs. Presenting case studies, experience and evaluation reports, and best practices in utilizing AI applications in IoT networks, it strikes a good balance between theoretical and practical issues. It also provides technical/scientific information on various aspects of AI technologies, ranging from basic concepts to research grade material, including future directions. The book is intended for researchers, practitioners, engineers and scientists involved in the design and development of protocols and AI applications for IoT-related devices. As the book covers a wide range of mobile applications and scenarios where IoT technologies can be applied, it also offers an essential introduction to the field.
Enterprise ontology is one of the conceptual pillars of enterprise engineering, next to enterprise design and enterprise governance, together accomplishing the goals of intellectual manageability, organisational concinnity and social devotion. By revealing the essence of an enterprise's organisation, enterprise ontology addresses business processes, data and rules in a fundamental and truly integrated way. In addition, it provides deep insight into and broad overview over complex organisational transformations. The book is divided into three parts. Part A is an introduction in enterprise engineering and enterprise ontology. Part B explores the theories underlying enterprise ontology, explaining the foundations of each theory, the elaborations in practical methods and techniques, and the relationships with other comparable approaches. Part C presents the practical application of the theories. It includes a comprehensive summary of the DEMO methodology and the DEMO specification language, as well as exercises and applications of DEMO in various business areas. It also features a chapter on combining DEMO with comparable approaches to modelling business processes, data and rules, to the benefit of the latter. Discussing the theoretical foundations of enterprise ontology and its practical applications in equal measure, this book is the principal textbook in courses on enterprise engineering. Since it unites elements from management science and information systems engineering, it is also relevant to students and professionals in either field.
This book constitutes selected papers from the 16th European, Mediterranean, and Middle Eastern Conference, EMCIS 2019, held in Dubai, UAE, in October 2019. EMCIS is dedicated to the definition and establishment of Information Systems as a discipline of high impact for the methodical community and IS professionals, focusing on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline.The 48 full papers presented in this volume were carefully reviewed and selected from a total of 138 submissions. They were organized in topical sections named: Big Data and Analytics; Blockchain Technology and Applications; Cloud Computing; Digital Services and Social Media; e-Government; Enterprise Information Systems; Health-Care Information Systems; Information Systems Security and Information Privacy Protection; Innovative Research Projects; IT Governance; and Management and Organizational Issues in Information Systems.