The rapid increase of web pages has introduced new challenges for many organizations as they attempt to extract information from a massive corpus of web pages. Finding relevant information, eliminating irregular content, and retrieving accurate results has become extremely difficult in today’s world where there is a surplus of information available. It is crucial to further understand and study web mining in order to discover the best ways to connect users with appropriate information in a timely manner. Advanced Practical Approaches to Web Mining Techniques and Application aims to illustrate all the concepts of web mining and fosters transformative, multidisciplinary, and novel approaches that introduce the practical method of analyzing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment. Covering a range of topics such as data science and security threats, this reference work is ideal for industry professionals, researchers, academicians, practitioners, scholars, instructors, and students.
In recent years, we have ushered in a new age where applications will become smaller, distributed, JavaScript-laden, microservices-infused, and utilize the hardware of the client to operate. A new paradigm has been forced upon us by the large search providers, and because of this, we can now leverage them to help our applications obtain influence where our applications become the voice of authority on the internet and consequently help our organizations reap the benefits of mass adoption. To better understand this, we must first consider the history that has taken us to where we find ourselves. Architectural Framework for Web Development and Micro Distributed Applications helps readers to come to an understanding of how the indexing domain may be leveraged by this new wave of JavaScript applications that have been termed micro distributed applications and by whose creation and implementation will allow the enterprise to reap the benefit of influence by the existing search systems that the masses utilize. It helps to fill in the picture of the evolution that has occurred and will continue to occur in web development whereby the new breed of applications will become JavaScript-laden and highly distributed and whereby the businesses that implement them will stand a chance to win the indexing race and consequently stand to win the attention of the masses. Covering topics such as distributed systems, search engine optimization, and software as a service, this premier reference source is a dynamic resource for web developers, students and educators of higher education, software developers, technical personnel, IT managers, computer scientists, librarians, researchers, and academicians.
The field of cybersecurity is becoming increasingly important due to the continuously expanding reliance on computer systems, the internet, wireless network standards such as Bluetooth and wi-fi, and the growth of "smart" devices, including smartphones, televisions, and the various devices that constitute the internet of things (IoT). Cybersecurity is also one of the significant challenges in the contemporary world, due to its complexity, both in terms of political usage and technology. The Handbook of Research on Cybersecurity Risk in Contemporary Business Systems examines current risks involved in the cybersecurity of various business systems today from a global perspective and investigates critical business systems. Covering key topics such as artificial intelligence, hacking, and software, this reference work is ideal for computer scientists, industry professionals, policymakers, researchers, academicians, scholars, instructors, and students.
Web Mining is moving the World Wide Web toward a more useful environment in which users can quickly and easily find the information they need. Web Mining uses document content, hyperlink structure, and usage statistics to assist users in meeting their needed information. This book provides a record of current research and practical applications in Web searching. It includes techniques that will improve the utilization of the Web by the design of Web sites, as well as the design and application of search agents. This book presents research and related applications in a manner that encourages additional work toward improving the reduction of information overflow, which is so common today in Web search results.
The rise of metaverse technologies has had a critical impact on the modern world. Due to the recent popularity of this technology, it is important to understand the strategies, opportunities, and challenges contained in the metaverse world in order to appropriately utilize it across fields. Strategies and Opportunities for Technology in the Metaverse World explores the opportunities and challenges facing the metaverse and considers the strategies and opportunities of metaverse technologies in various industries and countries. Covering a range of topics such as blockchain, artificial intelligence, virtual reality, and machine learning, this reference work is ideal for computer scientists, researchers, scholars, policymakers, academicians, practitioners, educators, and students.
In todays digital society, organizations must utilize technology in order to engage their audiences. Innovative game-like experiences are an increasingly popular way for businesses to interact with their customers; however, correctly implementing this technology can be a difficult task. To ensure businesses have the appropriate information available to successfully utilize gamification in their daily activities, further study on the best practices and strategies for implementation is required. The Handbook of Research on Gamification Dynamics and User Experience Design considers the importance of gamification in the context of organizations improvements and seeks to investigate game design from the experience of the user by providing relevant academic work, empirical research findings, and an overview of the field of study. Covering topics such as digital ecosystems, distance learning, and security awareness, this major reference work is ideal for policymakers, technology developers, managers, government officials, researchers, scholars, academicians, practitioners, instructors, and students.
In just the last few years, the visualization industry has arguably become the fastest-growing 3D industry and may soon overtake all others in total number of users. Just as the use of computer-aided design became the norm for nearly all architectural, engineering, and construction firms in the 1990s, 3D visualizations have become standard practice today. Autodesk® 3ds Max® is a powerful and versatile 3D software package that requires a thorough understanding in order to use it effectively. 3D Modeling Using Autodesk 3ds Max With Rendering View considers the challenges of learning 3ds Max®, focuses on the critical aspects of the program needed to produce stunning architectural visualizations, and discusses some of the fastest and most efficient ways to accomplish tasks. Covering a range of topics such as camera rendering and standard light effects, this reference work is ideal for researchers, academicians, scholars, practitioners, industry professionals, instructors, and students.
In recent years, falsification and digital modification of video clips, images, as well as textual contents have become widespread and numerous, especially when deepfake technologies are adopted in many sources. Due to adopted deepfake techniques, a lot of content currently cannot be recognized from its original sources. As a result, the field of study previously devoted to general multimedia forensics has been revived. The Handbook of Research on Advanced Practical Approaches to Deepfake Detection and Applications discusses the recent techniques and applications of illustration, generation, and detection of deepfake content in multimedia. It introduces the techniques and gives an overview of deepfake applications, types of deepfakes, the algorithms and applications used in deepfakes, recent challenges and problems, and practical applications to identify, generate, and detect deepfakes. Covering topics such as anomaly detection, intrusion detection, and security enhancement, this major reference work is a comprehensive resource for cyber security specialists, government officials, law enforcement, business leaders, students and faculty of higher education, librarians, researchers, and academicians.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
