Two authors with more than 40 years of combined library experience tap into their wealth of knowledge about discovery and user experience, sharing proven methods for setting up, promoting, and teaching their own discovery systems. Discovery systems are the new one-stop search model for libraries, but simply implementing the software doesn't ensure that it will meet your users' search needs. This book looks at how discovery systems are actually used by examining the findings of several user experience (UX) studies, providing data and observations that will inform your decisions about selecting, implementing, and enhancing this software. This book provides library practitioners who choose, administer, and interact with discovery systems with insight for establishing or fine-tuning a discovery system. You will understand how the use and effectiveness of the top discovery systems compare to more traditional databases and web resources, get insight into the comparative strengths and weaknesses of the best-selling discovery systems, and examine the UX research findings of the authors on student response and faculty response. You'll also learn about key configuration options that help or hinder search success with these systems and affect content selection, linking software setup, and interlibrary loan processes. The book concludes with recommended best practices for promoting discovery systems, including web design, placement on the library's website, getting coworkers on board, and PR ideas.

Updates the premier textbook for students and librarians needing to know the landscape of current databases and how to search them. Librarians need to know of existing databases, and they must be able to teach search capabilities and strategies to library users. This practical guide introduces librarians to a broad spectrum of fee-based and freely available databases and explains how to teach them. The updated 6th edition of this well-regarded text covers new databases on the market as well as updates to older databases. It also explains underlying information structures and demonstrates how to search most effectively. It introduces readers to several recent changes, such as the move away from metadata-based indexing to full text indexing by vendors covering newspaper content. Business databases receive greater emphasis. As in the previous editions, this book takes a real-world approach, covering topics from basic and advanced search tools to online subject databases. Each chapter includes a thorough discussion, a recap, concrete examples, exercises, and points to consider, making it an ideal text for courses in database searching as well as a trustworthy professional resource.

This essential guide covers the basics of planning to safeguard your library's digital assets—library catalog and circulation data, online resources, etc.—by taking advantage of cloud-based storage. Natural and human-made disasters, whether large-scale or as simple as accidental damage to an electrical circuit, can disrupt library operations and services by blocking access to the essential computer systems upon which we all rely. This book gives readers the basics of emergency planning and disaster preparedness for library digital assets, providing librarians with recovery planning tools and tips for making cloud-based disaster plans work for their libraries. Written by an expert with close to two decades' experience in library environment technology, Planning Cloud-Based Disaster Recovery for Digital Assets will help staff at libraries of all types make contingency plans for emergencies big and small. Readers will learn how thoughtful contingency and recovery plans can greatly mitigate damages caused by any number of unforeseen disasters and how cloud-based storage can serve to store and protect their library's digital assets. By following the book's recommendations to achieve digital redundant back-up, multiple access points, and larger storage capacity, a library can stay operational on the Internet despite emergencies that force building closures. Also included are appendixes of checklists for disaster planning and for evaluating cloud vendors as well as a comprehensive bibliography.

The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.

Web Portal Design, Implementation, Integration, and Optimization discusses the challenges faced in building web services and integrating applications in order to reach the successful benefits web portals bring to an organization. This collection of research aims to be a resource for researchers, developers, and industry practitioners involved in the technological, business, organizational and social dimensions of web portals.

This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.

In today's world, the pressing challenges of sustainable development and societal progress demand innovative solutions that harness the power of science and technology. From climate change to resource depletion and social inequalities, the urgency to find sustainable, intelligent, and ethical approaches has never been greater. Academic scholars and researchers play a crucial role in driving these advancements but often struggle to find comprehensive resources that bridge the gap between theory and real-world applications. The need of the hour is a definitive guide that unites expertise from diverse disciplines and offers practical insights into leveraging sustainable science and intelligent technologies to create meaningful societal development. Sustainable Science and Intelligent Technologies for Societal Development, edited by Brojo Kishore Mishra of GIET University, India, is the much-awaited solution to the challenges faced by academic scholars and researchers. This persuasive book brings together an esteemed collection of leading experts, academics, and industry professionals, all dedicated to addressing global challenges through the lens of applied sciences and intelligent technology applications. By presenting a wide range of innovative topics, such as renewable energy, smart healthcare, sustainable finance, and more, the book serves as a comprehensive resource that empowers scholars with actionable knowledge and innovative ideas. The book not only covers the theoretical aspects but also delves into the ethical considerations essential in shaping the future. In a world increasingly dependent on technology, it is vital to ensure that societal development aligns with principles of inclusivity, fairness, and environmental responsibility. With a focus on the United Nations Sustainable Development Goals (SDGs), the book provides a clear roadmap for scholars to contribute meaningfully to global progress. By offering concrete examples and real-world case studies, the book enables researchers to grasp the potential impact of their work, fostering collaborations that transcend traditional disciplinary boundaries. Sustainable Science and Intelligent Technologies for Societal Development is the go-to resource for academic scholars, scientists, researchers, innovators, industry professionals, and students who seek to be effective in the world. As a comprehensive guide that blends sustainable science and intelligent technologies with ethical considerations, this book equips its readers to create tangible solutions that address pressing global challenges. Through collective knowledge and interdisciplinary collaboration, this book stands as a beacon of hope and inspiration for driving meaningful societal development, paving the way for a more sustainable and prosperous future.

Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data Overcoming cyberattacks on mission-critical software systems by leveraging federated learning

Search Engine Optimization and Marketing: A Recipe for Success in Digital Marketing analyzes the web traffic for online promotion that includes search engine optimization and search engine marketing. After careful analysis of the nuances of the semantic web, of search engine optimization (SEO), and its practical set up, readers can put their best foot forward for SEO setup, link-building for SERP establishment, various methods with requisite algorithms, and programming codes with process inferences. The book offers comprehensive coverage of essential topics, including: • The concept of SEM and SEO • The mechanism of crawler program concepts of keywords • Keyword generation tools • Page ranking mechanism and indexing • Concepts of title, meta, alt tags • Concepts of PPC/PPM/CTR • SEO/SEM strategies • Anchor text and setting up • Query-based search While other books are focused on the traditional explanation of digital marketing, theoretical features of SEO and SEM for keyword set up with link-building, this book focuses on the practical applications of the above-mentioned concepts for effective SERP generation. Another unique aspect of this book is its abundance of handy workarounds to set up the techniques for SEO, a topic too often neglected by other works in the field. This book is an invaluable resource for social media analytics researchers and digital marketing students.

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.