This third volume on Database Semantics looks at the link between Artificial Intelligence and Databases / Information Systems. Database / Information System design, implementation and operation is a complex problem-solving task, where expert knowledge is needed. Use of Artificial Intelligence techniques and principles may help to acquire, represent and manipulate this knowledge, resulting in the enrichment of database semantics.
The number of new applications in need of database support is exploding and there is an increasing need to link and access database systems supporting these new applications via computer networks. End-users and non-computer experts are becoming heavily involved in the set-up, management and use of database systems and this book provides the important database design methodologies and implementation technology which should be available for them as well as for computer experts.
This book constitutes the refereed proceedings of the 13th International Baltic Conference on Databases and Information Systems, DB&IS 2018, held in Trakai, Lithuania, in July 2018. The 24 revised papers presented were carefully reviewed and selected from 69 submissions. The papers are centered around topics like information systems engineering, enterprise information systems, business process management, knowledge representation, ontology engineering, systems security, information systems applications, database systems, machine learning, big data analysis, big data processing, cognitive computing.
As humanity approaches the 3rd millennium, the sustainability of our present way of life becomes more and more questionable. New paradigms for the long-term coevolution of nature and civilization are urgently needed in order to avoid intolerable and irreversible modifications of our planetary environment. Earth System Analysis is a new scientific enterprise that tries to perceive the earth as a whole, a unique system which is to be analyzed with methods ranging from nonlinear dynamics to macroeconomic modelling. This book, resulting from an international symposium organized by the Potsdam Institute, has 2 aims: first, to integrate contributions from leading researchers and scholars from around the world to provide a multifaceted perspective of what Earth System Analysis is all about, and second, to outline the scope of the scientific challenge and elaborate the general formalism for a well-defined transdisciplinary discourse on this most fascinating issue.
There is a growing interest in developing intelligent systems that would enable users to accomplish complex tasks in a Web-centric environment with relative ease by utilizing such technologies as intelligent agents, distributed computing and computer supported collaborative work. This book brings together researchers in related fields to explore various aspects of ISS design and implementation, as well as to share experiences and lessons learned in deploying intelligent support systems.
Applications of Natural Language to Information Systems covers high academic quality papers on the following topics: natural language interfaces to databases, information retrieval, use of linguistic tools and electronic dictionaries, conceptual modelling, paraphrasing and validating information system models, the use of natural language as a specification interface for the design of information systems, linguistic aspects of database view integration and hypertext facilities for database querying. Furthermore the typical applications of natural language, are addressed, presented both from a scientific as well as an industrial perspective by Peter Chen, the inventor of the ER model, and Gerald Kristen, the founder of the KISS company. Other topics: - Natural Language Specification; - Natural Language Paraphrasing; - Linguistic Tools and Electronic Dictionaries; - Database Hypertext Facilities; - Information Retrieval; - Natural Language Database Interfaces; - Conceptual Modeling with Linguistic Knowledge; - Linguistic Aspects of Database View Integration.
Intelligence Science is an interdisciplinary subject dedicated to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain research on the principle and model of natural intelligence at the molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. Research scientists from the above three disciplines work together to explore new concepts, new theories, and methodologies.This book will introduce the concept and methodology of intelligence science systematically. The whole book is divided into 18 chapters altogether. It can be regarded as a textbook in courses of intelligence science, cognitive science, cognitive informatics etc. for senior and graduate students. It has important reference value for researchers engaged in fields such as intelligence science, brain science, cognitive science, neural science, artificial intelligence, psychology and so on.
Artificial Intelligence and cognitive science are the two fields devoted to the study and development of knowledge-based systems (KBS). Over the past 25years, researchers have proposed several approaches for modeling knowledge in KBS, including several kinds of formalism such as semantic networks, frames, and logics. In the early 1980s, J.F. Sowa introduced the conceptual graph (CG) theory which provides a knowledge representation framework consisting of a form of logic with a graph notationand integrating several features from semantic net and frame representations. Since that time, several research teams over the world have been working on the application and extension of CG theory in various domains ranging from natural language processing to database modeling and machine learning. This volume contains selected papers fromthe international conference on Conceptual Structures held in the city of Quebec, Canada, August 4-7, 1993. The volume opens with invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.
This volume contains revised and expanded versions of papers presented at the Seventh Annual Workshop on Conceptual Graphs, held at New Mexico State University in Las Cruces, and sponsored by the American Association for Artificial Intelligence and the NMSU Computer Science Department. The contents of the volume fall in the areas of representation issues, reasoning, data modeling and databases, algorithms and tools, and applications and natural language. One of the highlights reported in the volume is the landmark meeting of the first PEIRCE Project Workshop. The PEIRCE Project aims to build a state-of-the-art, industrial strength conceptual graphs workbench.
