Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Due to the development of mobile and Web 2.0 technology, knowledge transfer, storage and retrieval have become much more rapid. In recent years, there have been more and more new and interesting findings in the research field of knowledge management. This book aims to introduce readers to the recent research topics, it is titled "New Research on Knowledge Management Technology" and includes 13 chapters. In this book, new KM technologies and systems are proposed, the applications and potential of all KM technologies are explored and discussed. It is expected that this book provides relevant information about new research trends in comprehensive and novel knowledge management studies, and that it serves as an important resource for researchers, teachers and students, and for the development of practices in the knowledge management field.

Information technology. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Expert systems / knowledge-based systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research.

Artificial intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Expert systems / knowledge-based systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.

Natural language & machine translation --- Computational linguistics --- Artificial intelligence --- Machine learning --- Expert systems / knowledge-based systems --- Literature: history & criticism --- Semantics --- Natural Language Processing --- Computational Linguistics --- Artificial Intelligence --- explainable AI --- Artificial Neural Nets --- lexical semantics --- word vectors --- embeddings --- dynamic embeddings --- algebraic semantic --- knowledge bases --- machine learning

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.

Natural language & machine translation --- Data mining --- Algorithms & data structures --- Artificial intelligence --- Information technology: general issues --- Natural Language Processing (NLP) --- Data Mining and Knowledge Discovery --- Data Structures and Information Theory --- Artificial Intelligence --- Computer Applications --- Data Science --- Computer and Information Systems Applications --- Open Access --- financial opinion mining --- text mining in finance --- financial technology application --- FinTech --- argument mining in finance --- opinion quality evaluation --- numeral understanding --- Expert systems / knowledge-based systems --- Information theory

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years.

Software engineering. --- Management information systems. --- Automotive engineering. --- Special purpose computers. --- Software Engineering. --- Software Management. --- Automotive Engineering. --- Special Purpose and Application-Based Systems. --- Special purpose computers --- Computers --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Computer software engineering --- Engineering --- Communication systems --- Software Engineering --- Software Management --- Automotive Engineering --- Special Purpose and Application-Based Systems --- IT in Business --- Model-Driven Software Development --- Requirements Engineering --- Automotive Software Engineering --- Embedded Systems --- Open Access --- SPES Methodology --- Simulation --- Co-Design of Systems --- Business mathematics & systems --- Business applications --- Automotive technology & trades --- Automotive (motor mechanic) skills --- Expert systems / knowledge-based systems