This volume contains the lecture notes of the 9th Reasoning Web Summer School 2013, held in Mannheim, Germany, in July/August 2013. The 2013 summer school program covered diverse aspects of Web reasoning, ranging from scalable lightweight formalisms such as RDF to more expressive ontology languages based on description logics. It also featured foundational reasoning techniques used in answer set programming and ontology-based data access as well as emerging topics like geo-spatial information handling and reasoning-driven information extraction and integration.

This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.

This volume contains 8 lecture notes of the 16th Reasoning Web Summer School (RW 2020), held in Oslo, Norway, in June 2020. The Reasoning Web series of annual summer schools has become the prime educational event in the field of reasoning techniques on the Web, attracting both young and established researchers. The broad theme of this year's summer school was “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures have been presented during the school: Introduction to Probabilistic Ontologies, On the Complexity of Learning Description Logic Ontologies, Explanation via Machine Arguing, Stream Reasoning: From Theory to Practice, First-Order Rewritability of Temporal Ontology-Mediated Queries, An Introduction to Answer Set Programming and Some of Its Extensions, Declarative Data Analysis using Limit Datalog Programs, and Knowledge Graphs: Research Directions.

This book features high-quality research papers presented at Third Doctoral Symposium on Computational Intelligence (DoSCI 2022), organized by Institute of Engineering and Technology (IET), AKTU, Lucknow, India, on March 5, 2022. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high performance computing, biomedical computing, and decision support and decision making.

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems.

This book presents the proceedings of the International Conference on Managing Business through Web Analytics (ICMBWA 2021). The conference provides a global forum for sharing knowledge and results in theory, methodology, and applications of Web Analytics and their role in the formulation and the orientation of businesses’ strategies. The aim of the conference is to provide a platform for researchers and practitioners from both academia and industry to meet and share their works in the field. Is an excellent resource for scholars, experts and industrial in the fields represented, as well as Ph.D. students seeking an entryway into current research in data analytics, Web analytics, machine learning algorithms, and their various applications within businesses.

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.