Semantic Web

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The Semantic Web is a "web of data" that facilitates machines to understand the semantics, or meaning, of information on the World Wide Web. (

Conferences related to Semantic Web

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2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore

2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)

The conference will provide a forum for discussions and presentations of advancements inknowledge, new methods and technologies relevant to industrial electronics, along with their applications and future developments.

2019 IEEE International Conference on Industrial Technology (ICIT)

The scope of the conference will cover, but will not be limited to, the following topics: Robotics; Mechatronics; Industrial Automation; Autonomous Systems; Sensing and artificial perception, Actuators and Micro-nanotechnology; Signal/Image Processing and Computational Intelligence; Control Systems; Electronic System on Chip and Embedded Control; Electric Transportation; Power Electronics; Electric Machines and Drives; Renewable Energy and Smart Grid; Data and Software Engineering, Communication; Networking and Industrial Informatics.

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC2019) will be held in the south of Europe in Bari, one of the most beautiful and historical cities in Italy. The Bari region’s nickname is “Little California” for its nice weather and Bari's cuisine is one of Italian most traditional , based of local seafood and olive oil. SMC2019 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report up-to-the-minute innovations and developments, summarize state­of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems and cybernetics. Advances have importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience, and thereby improve quality of life.

2019 IEEE International Professional Communication Conference (ProComm)

The scope of the conference includes the study, development, improvement, and promotion ofeffective techniques for preparing, organizing, processing, editing, collecting, conserving,teaching, and disseminating any form of technical information by and to individuals and groupsby any method of communication. It also includes technical, scientific, industrial, and otheractivities that contribute to the techniques and products used in this field.

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Periodicals related to Semantic Web

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Fuzzy Systems, IEEE Transactions on

Theory and application of fuzzy systems with emphasis on engineering systems and scientific applications. (6) (IEEE Guide for Authors) Representative applications areas include:fuzzy estimation, prediction and control; approximate reasoning; intelligent systems design; machine learning; image processing and machine vision;pattern recognition, fuzzy neurocomputing; electronic and photonic implementation; medical computing applications; robotics and motion control; constraint propagation and optimization; civil, chemical and ...

Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.

Industrial Informatics, IEEE Transactions on

IEEE Transactions on Industrial Informatics focuses on knowledge-based factory automation as a means to enhance industrial fabrication and manufacturing processes. This embraces a collection of techniques that use information analysis, manipulation, and distribution to achieve higher efficiency, effectiveness, reliability, and/or security within the industrial environment. The scope of the Transaction includes reporting, defining, providing a forum for discourse, and informing ...

Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.

Intelligent Systems, IEEE

IEEE Intelligent Systems, a bimonthly publication of the IEEE Computer Society, provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product. The magazine serves software engineers, systems ...

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Most published Xplore authors for Semantic Web

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Xplore Articles related to Semantic Web

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Semantic Web and semantic Web services: father and son or indivisible twins?

[{u'author_order': 1, u'affiliation': u'Digital Enterprise Res. Inst., Innsbruck Univ., Austria', u'authorUrl': u'', u'full_name': u'M. Hepp', u'id': 37427499300}] IEEE Internet Computing, 2006

The semantic Web is, without a doubt, gaining momentum in both industry and academia. The recent International Semantic Web Conference (ISWC) attracted more than 500 researchers; major vendors including IBM, Oracle, and Software AG have released or announced products; and the forthcoming Semantic Technology Conference in San Jose, California, is poised to be an impressive showcase for executives and venture ...

Rule-based intelligence in the Semantic Web-or-"I'll settle for a web that's just not so dumb!"

[{u'author_order': 1, u'affiliation': u'TopQuadrant, Inc.', u'authorUrl': u'', u'full_name': u'Dean Allemang', u'id': 37564921100}] 2006 Second International Conference on Rules and Rule Markup Languages for the Semantic Web (RuleML'06), 2006

One could fairly say that the role of rules in the semantic Web has been controversial; in the few short years since the first publication of the semantic Web stack, Rules have sometimes been given a central role, at other times a peripheral role, and sometimes left out completely. Why such variation for an technology with thirty years of background? ...

A Relation-Based Page Rank Algorithm for Semantic Web Search Engines

[{u'author_order': 1, u'affiliation': u'Politecnico di Torino, Torino', u'authorUrl': u'', u'full_name': u'Fabrizio Lamberti', u'id': 37394958100}, {u'author_order': 2, u'affiliation': u'Politecnico di Torino, Torino', u'authorUrl': u'', u'full_name': u'Andrea Sanna', u'id': 37351391600}, {u'author_order': 3, u'affiliation': u'Politecnico di Torino, Torino', u'authorUrl': u'', u'full_name': u'Claudio Demartini', u'id': 37353013100}] IEEE Transactions on Knowledge and Data Engineering, 2009

With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general-purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming ...

Using Semantic Web Technologies in a Web Based System for Personalized Learning AI Course

[{u'author_order': 1, u'authorUrl': u'', u'full_name': u'Foteini Grivokostopoulou', u'id': 38517302400}, {u'author_order': 2, u'authorUrl': u'', u'full_name': u'Isidoros Perikos', u'id': 38521020300}, {u'author_order': 3, u'authorUrl': u'', u'full_name': u'Ioannis Hatzilygeroudis', u'id': 37265420000}] 2014 IEEE Sixth International Conference on Technology for Education, 2014

Utilization of semantic web technologies in educational systems is rapidly expanded, bringing new and more efficient teaching and learning capabilities. Semantic Web Based Educational Systems (SWBEs) rely on semantic web technologies and are proved to be more intelligent and personalized to the students learning needs. In this paper, we present a semantic web based adaptive educational system that is developed ...

Semantic Web Service Similarity Ranking Proposal Based on Semantic Space Vector Model

[{u'author_order': 1, u'full_name': u'ZhiHao Zeng'}, {u'author_order': 2, u'full_name': u'JiPing Hu'}, {u'author_order': 3, u'full_name': u'Ting Dong'}, {u'author_order': 4, u'full_name': u'Yu Wang'}] 2012 Second International Conference on Intelligent System Design and Engineering Application, 2012

With the Semantic Web services technology research work continued to deepen, the number of semantic Web services on the Internet has dramatically increased how to locate available semantic Web services quickly and easily has become an urgent and key issue. Among semantic Web service matchmaking technology study, one of the important research themes is the semantic Web service matchmaking result ...

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Educational Resources on Semantic Web

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No eLearning Articles are currently tagged "Semantic Web"


  • Complex Relationships for the Semantic Web

    This chapter contains sections titled: Introduction, Knowledge Modeling, Information Scapes, Knowledge Discovery, Visual Interfaces, Related Work, Conclusion, Notes, References

  • Social Semantic Web Mining

    The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro). Table of Contents: Acknowledgments / Grant Aid / Introduction and the Web / Web Mining / The Social Web / The Semantic Web / The Social Semantic Web / Social Semantic Web Mining / Social Semantic Web Mining of Communities / Social Semantic Web Mining of Groups / Social Semantic Web Mining of Users / Conclusions / Bibliography / Authors' Biographies

  • Publishing and Using Cultural Heritage Linked Data on the Semantic Web

    Cultural Heritage (CH) data is syntactically and semantically heterogeneous, multilingual, semantically rich, and highly interlinked. It is produced in a distributed, open fashion by museums, libraries, archives, and media organizations, as well as individual persons. Managing publication of such richness and variety of content on the Web, and at the same time supporting distributed, interoperable content creation processes, poses challenges where traditional publication approaches need to be re-thought. Application of the principles and technologies of Linked Data and the Semantic Web is a new, promising approach to address these problems. This development is leading to the creation of large national and international CH portals, such as Europeana, to large open data repositories, such as the Linked Open Data Cloud, and massive publications of linked library data in the U.S., Europe, and Asia. Cultural Heritage has become one of the most successful application domains of Linked Data and Semantic Web technologies. This book gives an overview on why, when, and how Linked (Open) Data and Semantic Web technologies can be employed in practice in publishing CH collections and other content on the Web. The text first motivates and presents a general semantic portal model and publishing framework as a solution approach to distributed semantic content creation, based on an ontology infrastructure. On the Semantic Web, such an infrastructure includes shared metadata models, ontologies, and logical reasoning, and is supported by shared ontology and other Web services alleviating the use of the new technology and linked data in legacy cataloging systems. The goal of all this is to provide layman users and researchers with new, more intelligent and usable Web applications that can be utilized by other Web applications, too, via well-defined Application Programming Interfaces (API). At the same time, it is possible to provide publishing organizations with more cost-efficient solutions for content creation and publication. This book is targeted to computer scientists, museum curators, librarians, archivists, and other CH professionals interested in Linked Data and CH applications on the Semantic Web. The text is focused on practice and applications, making it suitable to students, researchers, and practitioners developing Web services and applications of CH, as well as to CH managers willing to understand the technical issues and challenges involved in linked data publication. Table of Contents: Cultural Heritage on the Semantic Web / Portal Model for Collaborative CH Publishing / Requirements for Publishing Linked Data / Metadata Schemas / Domain Vocabularies and Ontologies / Logic Rules for Cultural Heritage / Cultural Content Creation / Semantic Services for Human and Machine Users / Conclusions

  • Semantic Gadgets: Ubiquitous Computing Meets the Semantic Web

    This chapter contains sections titled: Introduction, About Representation, Scenario: Semantic Gadget in a Museum, Semantic Discovery, Contracting for the Use of Services, Composition of Services, Museum Scenario Revisited: An Analysis, Conclusion, References

  • Libraries and the Semantic Web: An Introduction to Its Applications and Opportunities for Libraries

    This book covers the concept of the Semantic Web—what it is, the components that comprise it, including Linked Data, and the various ways that libraries are engaged in contributing to its development in making library resources and services ever more accessible to end-users.

  • Natural Language Processing as a Foundation of the Semantic Web

    Natural Language Processing as a Foundation of the Semantic Web argues that Natural Language Processing (NLP) does, and will continue to, underlie the Semantic Web (SW), including its initial construction from unstructured sources like the World Wide Web, in several different ways, and whether its advocates realise this or not. Chiefly, it argues, such NLP activity is the only way up to a defensible notion of meaning at conceptual levels based on lower level empirical computations over usage. The claim being made is definitely not logic-bad, NLP-good in any simple-minded way, but that the SW will be a fascinating interaction of these two methodologies, like the WWW (which, as the authors explain, has been a fruitful field for statistical NLP research) but with deeper content. Only NLP technologies (and chiefly information extraction) will be able to provide the requisite resource description framework (RDF) knowledge stores for the SW from existing WWW (unstructured) text databases, and in the vast quantities needed. There is no alternative at this point, since a wholly or mostly hand-crafted SW is also unthinkable, as is a SW built from scratch and without reference to the WWW. It is also assumed here that, whatever the limitations on current SW representational power drawn attention to here, the SW will continue to grow in a distributed manner so as to serve the needs of scientists, even if it is not perfect. The WWW has already shown how an imperfect artefact can become indispensable. Natural Language Processing as a Foundation of the Semantic Web will appeal to researchers, practitioners and anyone with an interest in NLP, the philosophy of language, cognitive science, the Semantic Web and Web Science generally, as well as providing a magisterial and controversial overview of the history of artificial intelligence

  • The Epistemology of Intelligent Semantic Web Systems

    The Semantic Web is a young discipline, even if only in comparison to other areas of computer science. Nonetheless, it already exhibits an interesting history and evolution. This book is a reflection on this evolution, aiming to take a snapshot of where we are at this specific point in time, and also showing what might be the focus of future research. This book provides both a conceptual and practical view of this evolution, especially targeted at readers who are starting research in this area and as support material for their supervisors. From a conceptual point of view, it highlights and discusses key questions that have animated the research community: what does it mean to be a Semantic Web system and how is it different from other types of systems, such as knowledge systems or web-based information systems? From a more practical point of view, the core of the book introduces a simple conceptual framework which characterizes Intelligent Semantic Web Systems. We describe this framework, the components it includes, and give pointers to some of the approaches and technologies that might be used to implement them. We also look in detail at concrete systems falling under the category of Intelligent Semantic Web Systems, according to the proposed framework, allowing us to compare them, analyze their strengths and weaknesses, and identify the key fundamental challenges still open for researchers to tackle.

  • Natural Language Processing for the Semantic Web

    This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.

  • SEmantic portAL: The SEAL Approach

    This chapter contains sections titled: Introduction, Ontologies and Knowledge Bases, Ontology Engineering, SEAL Infrastructure and Core Modules, Semantic Ranking, Semantic Personalization, RDF Outside: From a Semantic Web Site to the Semantic Web, Related Work, Conclusion, Acknowledgments, Notes, References

  • Incentive-Centric Semantic Web Application Engineering

    While many Web 2.0-inspired approaches to semantic content authoring do acknowledge motivation and incentives as the main drivers of user involvement, the amount of useful human contributions actually available will always remain a scarce resource. Complementarily, there are aspects of semantic content authoring in which automatic techniques have proven to perform reliably, and the added value of human (and collective) intelligence is often a question of cost and timing. The challenge that this book attempts to tackle is how these two approaches (machine- and human-driven computation) could be combined in order to improve the cost-performance ratio of creating, managing, and meaningfully using semantic content. To do so, we need to first understand how theories and practices from social sciences and economics about user behavior and incentives could be applied to semantic content authoring. We will introduce a methodology to help software designers to embed incentives-minded functionalities into semantic applications, as well as best practices and guidelines. We will present several examples of such applications, addressing tasks such as ontology management, media annotation, and information extraction, which have been built with these considerations in mind. These examples illustrate key design issues of incentivized Semantic Web applications that might have a significant effect on the success and sustainable development of the applications: the suitability of the task and knowledge domain to the intended audience, and the mechanisms set up to ensure high-quality contributions, and extensive user involvement. Table of Contents: Semantic Data Management: A Human-driven Process / Fundamentals of Motivation and Incentives / Case Study: Motivating Employees to Annotate Content / Case Study: Building a Community of Practice Around Web Service Management and Annotation / Case Study: Games with a Purpose for Semantic Content Creation / Conclusions

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