Download or read book Learning Ontology Relations by Combining Corpus Based Techniques and Reasoning on Data from Semantic Web Sources written by Gerhard Wohlgenannt and published by Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach.
Download or read book The Cyber Meta Reality written by Joshua A. Sipper and published by Rowman & Littlefield. This book was released on 2022-04-04 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: As one begins to explore the many complexities of quantum computing, nanotechnology, and AI, it becomes clear that there is an underlying reality within cyberspace that is comprised of other realities and that these realities all have their own biomes, ecosystems, and microbiomes built on information, energy, and human creative reality and potential. It is clear that there has not been much research on this , especially the piece dealing with the cyber microbiome, which looks at the part of the iceberg that is “under the surface” and makes up most of cyberspace, much like how our human microbiome is many orders of magnitude larger than our human cells. The microbiome is extremely important from the perspective of how to treat diseases in humans, especially bacterial infections. The same is true for how to treat “diseases” in the cyber meta-reality. Thus, knowing all we can about the cyber meta-reality, biome, and microbiome is absolutely necessary in ensuring this world’s growth, care, and flourishing.
Download or read book The Semantic Web Trends and Challenges written by Valentina Presutti and published by Springer. This book was released on 2014-05-09 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Crete, Greece France, in May 2014. The 50 revised full papers presented together with three invited talks were carefully reviewed and selected from 204 submissions. They are organized in topical sections on mobile, sensor and semantic streams; services, processes and cloud computing; social web and web science; data management; natural language processing; reasoning; machine learning, linked open data; cognition and semantic web; vocabularies, schemas, ontologies. The book also includes 11 papers presented at the PhD Symposium.
Download or read book Law Ontologies and the Semantic Web written by Joost Breuker and published by IOS Press. This book was released on 2009 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on workshops and conferences on Artificial Intelligence (AI) and Law, this work deals with legal ontologies and Semantic Web applications, covering both theoretical aspects and practical systems.
Download or read book Ontology Learning for the Semantic Web written by Alexander Maedche and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process. Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.
Download or read book Ontology Learning from Text written by Paul Buitelaar and published by IOS Press. This book was released on 2005 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest title in Black Library's premium line. Perturabo - master of siegecraft, and executioner of Olympia. Long has he lived in the shadow of his more favoured primarch brothers, frustrated by the mundane and ignominious duties which regularly fall to his Legion. When Fulgrim offers him the chance to lead an expedition in search of an ancient and destructive xenos weapon, the Iron Warriors and the Emperor's Children unite and venture deep into the heart of the great warp-rift known only as 'the Eye'. Pursued by a ragged band of survivors from Isstvan V and the revenants of a dead eldar world, they must work quickly if they are to unleash the devastating power of the Angel Exterminatus
Download or read book Data Integration in the Life Sciences written by Patrick Lambrix and published by Springer. This book was released on 2010-08-19 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development and increasingly widespread deployment of high-throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The development of these models often requires integration of diverse experimental data resources; once constructed, the models themselves become data and present new integration challenges for tasks such as interpretation, validation and comparison. The Data Integration in the Life Sciences (DILS) Conference series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and in particular, evolution, matching and debugging of ontologies, akeycomponentforsemanticintegration;Web servicesasanimportanttechn- ogy for data integration in the life sciences; data and text mining techniques for discovering and recognizing biomedical entities and relationships between these entities; and information management, introducing data integration solutions for di?erent types of applications related to cancer, systems biology and - croarray experimental data, and an approach for integrating ranked data in the life sciences.
Download or read book Perspectives on Ontology Learning written by J. Lehmann and published by IOS Press. This book was released on 2014-04-03 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the creation of simple taxonomical structures, as well as on problems specifically related to knowledge modeling and representation using the Web Ontology Language. Perspectives on Ontology Learning is designed for researchers in the field of semantic technologies and developers of knowledge-based applications. It covers various aspects of ontology learning including ontology quality, user interaction, scalability, knowledge acquisition from heterogeneous sources, as well as the integration with ontology engineering methodologies.
Download or read book Learning Expressive Ontologies written by Johanna Völker and published by . This book was released on 2009 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ontological Engineering written by Asunción Gómez-Pérez and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.
Download or read book Exploiting Semantic Web Knowledge Graphs in Data Mining written by P. Ristoski and published by IOS Press. This book was released on 2019-06-28 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.
Download or read book Knowledge Graphs and Big Data Processing written by Valentina Janev and published by Springer Nature. This book was released on 2020-07-15 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Download or read book Semantic Similarity from Natural Language and Ontology Analysis written by Sébastien Harispe and published by Morgan & Claypool Publishers. This book was released on 2015-05-01 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better understanding of semantic similarity estimation and more generally semantic measures. To this end, we propose an in-depth characterization of existing proposals by discussing their features, the assumptions on which they are based and empirical results regarding their performance in particular applications. By answering these questions and by providing a detailed discussion on the foundations of semantic measures, our aim is to give the reader key knowledge required to: (i) select the more relevant methods according to a particular usage context, (ii) understand the challenges offered to this field of study, (iii) distinguish room of improvements for state-of-the-art approaches and (iv) stimulate creativity toward the development of new approaches. In this aim, several definitions, theoretical and practical details, as well as concrete applications are presented
Download or read book ECAI 2010 written by European Coordinating Committee for Artificial Intelligence and published by IOS Press. This book was released on 2010 with total page 1184 pages. Available in PDF, EPUB and Kindle. Book excerpt: LC copy bound in 2 v.: v. 1, p. 1-509; v. 2, p. [509]-1153.
Download or read book Ontology Matching written by Jérôme Euzenat and published by Springer Science & Business Media. This book was released on 2007-06-15 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontologies are viewed as the silver bullet for many applications, but in open or evolving systems, different parties can adopt different ontologies. This increases heterogeneity problems rather than reducing heterogeneity. This book proposes ontology matching as a solution to the problem of semantic heterogeneity, offering researchers and practitioners a uniform framework of reference to currently available work. The techniques presented apply to database schema matching, catalog integration, XML schema matching and more.
Download or read book Innovations Developments and Applications of Semantic Web and Information Systems written by Lytras, Miltiadis D. and published by IGI Global. This book was released on 2018-01-19 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, there has been an increased advancement and evolution in semantic web and information systems in a variety of fields. The integration of these approaches to ontology engineering, sophisticated methods and algorithms for open linked data extraction, and advanced decision-making creates new opportunities for a bright future. Innovations, Developments, and Applications of Semantic Web and Information Systems is a critical scholarly resource that discusses integrated methods of research and analytics in information technology. Featuring coverage on a broad range of topics, such as cognitive computing, artificial intelligence, machine learning, data analysis, and algorithms, this book is geared towards researchers, academicians, and professionals seeking current information on semantic web and information systems.
Download or read book Semantic Data Mining written by A. Ławrynowicz and published by IOS Press. This book was released on 2017-04-18 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.
