Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.

"This book presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, human-computer interaction, and more"--Provided by publisher.

This book constitutes the refereed proceedings of the 4th International Conference on Advances in Information Systems, ADVIS 2006, held in Izmir, Turkey in October 2006. The 38 revised full papers presented together with four invited lectures were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections.

This book offers comprehensive coverage of information retrieval by considering both Text Based Information Retrieval (TBIR) and Content Based Image Retrieval (CBIR), together with new research topics. The approach to TBIR is based on creating a thesaurus, as well as event classification and detection. N-gram thesaurus generation for query refinement offers a new method for improving the precision of retrieval, while event classification and detection approaches aid in the classification and organization of information using web documents for domain-specific retrieval applications. In turn, with regard to content based image retrieval (CBIR) the book presents a histogram construction method, which is based on human visual perceptions of color. The book’s overarching goal is to introduce readers to new ideas in an easy-to-follow manner.

This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data Mining and Internet of Things (IoT). It gathers papers presented at ICETIT 2019, the 1st International Conference on Emerging Trends in Information Technology, which was held in Delhi, India, in June 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, data analytics and cloud computing, security and privacy, and next generation computing technologies.

Intelligent Transportation Systems (ITS) are the model for integrating advanced information technology, data communication transmission technology, electronic sensing technology, control technology and computer technology into a comprehensive ground traffic management system. They are the direction of development for future transportation systems. This book presents the proceedings of the 3rd International Conference on Information Technology and Intelligent Transportation Systems (ITITS 2018), held in Xi’an, China, on 15-16 September 2018. The conference provides a platform for professionals and researchers from industry and academia to present and discuss recent advances in the field of information technology and intelligent transportation systems. Intelligent transport systems vary in the technologies they apply, from basic management systems to more application-based systems. Information technology – including wireless communication, computational technologies, floating car data/floating cellular data, sensor technologies, and video vehicle detection – is also intrinsic to intelligent transportation systems. All papers were reviewed by 3-4 referees, and the program chairs of the conference committee made their selections based on the score of each paper. This year, ITITS 2018 received more than 168 papers from 4 countries, of which 41 papers were accepted. Offering a state-of-the-art overview of the theoretical and applied topics related to ITS, this book will be of interest to all those working in the field.

The service industry is continually improving, forcing service-oriented engineering to improve alongside it. In a digitalized world, technology within the service industry has adapted to support interactions between users and organizations. By identifying key problems and features, service providers can help increase facilitator profitability and user satisfaction. Multidisciplinary Approaches to Service-Oriented Engineering is a well-rounded collection of research that examines methods of providing optimal system design for service systems and applications engineering. While exploring topics such as cloud ecosystems, interface localization, and requirement prioritization, this publication provides information about the approaches and development of software architectures to improve service quality. This book is a vital resource for engineers, theoreticians, educators, developers, IT consultants, researchers, practitioners, and professionals.

The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.

We were very pleased to once again extend to the delegates and, we are pleased to th say, our friends the warmest of welcomes to the 8 International Conference on Knowledge-Based Intelligent Information and Engineering Systems at Wellington - stitute of Technology in Wellington, New Zealand. The KES conferences attract a wide range of interest. The broad focus of the c- ference series is the theory and applications of computational intelligence and em- gent technologies. Once purely a research field, intelligent systems have advanced to the point where their abilities have been incorporated into many conventional appli- tion areas. The quest to encapsulate human knowledge and capabilities in domains such as reasoning, problem solving, sensory analysis, and other complex areas has been avidly pursued. This is because it has been demonstrated that these abilities have definite practical applications. The techniques long ago reached the point where they are being exploited to provide commercial advantages for companies and real beneficial effects on profits. KES 2004 provided a valuable mechanism for delegates to obtain a profound view of the latest intelligent systems research into a range of - gorithms, tools and techniques. KES 2004 also gave delegates the chance to come into contact with those applying intelligent systems in diverse commercial areas. The combination of theory and practice represents a uniquely valuable opportunity for - preciating the full spectrum of intelligent-systems activity and the “state of the art”.

• Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. • Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. • Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include: • Mining Biomedical Literature and Clinical Narratives • Medication Information Extraction • Machine Learning Techniques for Mining Medical Search Queries • Detecting the Level of Personal Health Information Revealed in Social Media • Curating Layperson’s Personal Experiences with Health Care from Social Media and Twitter • Health Dialogue Systems for Improving Access to Online Content • Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired • Semantic-based Visual Information Retrieval for Mining Radiographic Image Data • Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions