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Ontology-Based Information Retrieval for Healthcare Systems
With the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and cover...
Ontologies
This book describes the state-of-the-art in ontology-driven information systems (ODIS) and gives a complete perspective on the problems, solutions and open research questions in this field. The book covers four broad areas: foundations of ODIS, ontological engineering, ODIS architectures, and ODIS applications. It will trigger innovative thought processes and open up significant new domains in ODIS research.
Terminological Ontologies
Information infrastructures are integrated solutions based on the fusion of information and communication technologies. They are characterized by the large amount of data that must be managed accordingly. An information infrastructure requires an efficient and effective information retrieval system to provide access to the items stored in the infrastructure. Terminological Ontologies: Design, Management and Practical Applications presents the main problems that affect the discovery systems of information infrastructures to manage terminological models, and introduces a combination of research tools and applications in Semantic Web technologies. This book specifically analyzes the need to cre...
Information Retrieval. An Ontology-based Approach
Scientific Study from the year 2020 in the subject Computer Science - General, language: English, abstract: Information shared over the web keeps escalating gradually and rapidly. Due to this fast and steady growth, well-known problems are associated with retrieving desired information when needed. However, a few initiatives were introduced in the previous decade with the development of search engine technology. The search engine technology aids in the collection, storage and pre-processing a wide range of information to deliver relevant resources instantly in response to users' needs. Nevertheless, users sometimes need more effort to obtain desired information. This paper discusses the concept of information retrieval with some emphasis on the different information retrieval models. Furthermore, this paper will describe how documents are analyzed and ranked using different models.
Cross Language Information Retrieval Using Ontologies
The basic idea behind a Cross Language Information Retrieval (CLIR) system is to retrieve documents in a language different from the query. Therefore translation is needed before matching of query and document terms can take place. This translation process tends to cause a reduction in the retrieval effectiveness of CUR as compared to monolingual Information Retrieval systems. The research introduces a new CUR approach, by producing a unique CUR system based on multilingual Arabic/English ontologies; the ontology is used for query expansion and translation. Both Arabic and English ontologies are mapped using unique automatic ontology mapping tools that will be introduced in this study as wel...
Law and the Semantic Web
by Roberto Cencioni At the Lisbon Summit in March 2000, European heads of state and government set a new goal for the European Union — to become the most competitive knowled- based society in the world by 2010. As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens — at some points in their lives — have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important ...
Ontology Learning and Population from Text
In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Ontologies:
Ontologies have been developed and investigated for quite a while now in artificial intelligence and natural language processing to facilitate knowledge sharing and reuse. More recently, the notion of ontologies has attracted attention from fields such as intelligent information integration, cooperative information systems, information retrieval, electronic commerce, and knowledge management. The author systematically introduces the notion of ontologies to the non-expert reader and demonstrates in detail how to apply this conceptual framework for improved intranet retrieval of corporate information and knowledge and for enhanced Internet-based electronic commerce. In the second part of the book, the author presents a more technical view on emerging Web standards, like XML, RDF, XSL-T, or XQL, allowing for structural and semantic modeling and description of data and information.
Knowledge-Driven Multimedia Information Extraction and Ontology Evolution
This book presents the state of the art in the areas of ontology evolution and knowledge-driven multimedia information extraction, placing an emphasis on how the two can be combined to bridge the semantic gap. This was also the goal of the EC-sponsored BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction) project, to which the authors of this book have all contributed. The book addresses researchers and practitioners in the field of computer science and more specifically in knowledge representation and management, ontology evolution, and information extraction from multimedia data. It may also constitute an excellent guide to students attending courses within a computer science study program, addressing information processing and extraction from any type of media (text, images, and video). Among other things, the book gives concrete examples of how several of the methods discussed can be applied to athletics (track and field) events.
Ontological Engineering
Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web....
