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INFOCOMP / Datasys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing
INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing June 28, 2017, Venice, Italy The Seventh International Conference on Advanced Communications and Computation (INFOCOMP 2017) The Seventh International Conference on Advances in Information Mining and Management (IMMM 2017) The Twelfth International Conference on Internet and Web Applications and Services (ICIW 2017) INFOCOMP/IMMM/ICIW (DataSys) June 25{29, 2017 - Venice, Italy INFOCOMP, June 25 { 29, 2017 - Venice, Italy INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP Expert Panel: Web Semantic Mapping & Information Proc. INFOCOMP Expert Panel: Web Semantic Mapping & Information Proc. Panelists Claus-Peter R¨uckemann (Moderator), Westf¨alischeWilhelms-Universit¨atM¨unster(WWU) / Leibniz Universit¨atHannover / North-German Supercomputing Alliance (HLRN), Germany Marc Jansen, University of Applied Sciences Ruhr West, Deutschland Fahad Muhammad, CSTB, Sophia Antipolis, France Kiyoshi Nagata, Daito Bunka University, Japan Claus-Peter R¨uckemann, WWU M¨unster/ Leibniz Universit¨atHannover / HLRN, Germany INFOCOMP 2017: http://www.iaria.org/conferences2017/INFOCOMP17.html Program: http://www.iaria.org/conferences2017/ProgramINFOCOMP17.html -
May 28, 2016 3:46 WSPC/INSTRUCTION FILE Output
May 28, 2016 3:46 WSPC/INSTRUCTION FILE output International Journal of Semantic Computing c World Scientific Publishing Company Methods and Resources for Computing Semantic Relatedness Yue Feng Ryerson University Toronto, Ontario, Canada [email protected] Ebrahim Bagheri Ryerson University Toronto, Ontario, Canada [email protected] Received (Day Month Year) Revised (Day Month Year) Accepted (Day Month Year) Semantic relatedness (SR) is defined as a measurement that quantitatively identifies some form of lexical or functional association between two words or concepts based on the contextual or semantic similarity of those two words regardless of their syntactical differences. Section 1 of the entry outlines the working definition of semantic related- ness and its applications and challenges. Section 2 identifies the knowledge resources that are popular among semantic relatedness methods. Section 3 reviews the primary measurements used to calculate semantic relatedness. Section 4 reviews the evaluation methodology which includes gold standard dataset and methods. Finally, Section 5 in- troduces further reading. In order to develop appropriate semantic relatedness methods, there are three key aspects that need to be examined: 1) the knowledge resources that are used as the source for extracting semantic relatedness; 2) the methods that are used to quantify semantic relatedness based on the adopted knowledge resource; and 3) the datasets and methods that are used for evaluating semantic relatedness techniques. The first aspect involves the selection of knowledge bases such as WordNet or Wikipedia. Each knowledge base has its merits and downsides which can directly affect the accurarcy and the coverage of the semantic relatedness method. The second aspect relies on different methods for utilizing the beforehand selected knowledge resources, for example, methods that depend on the path between two words, or a vector representation of the word. -
An Extensible Platform for Semantic Classification and Retrieval of Multimedia Resources
An extensible platform for semantic classification and retrieval of multimedia resources Paolo Pellegrino, Fulvio Corno Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129, Torino, Italy {paolo.pellegrino, fulvio.corno}@polito.it Abstract and seem very promising, but are still mostly exploited for textual resources only. In effect, text is the simplest form This paper introduces a possible solution to the problem of knowledge representation which can be both of semantic indexing, searching and retrieving heterogeneous understood by humans and quickly processed by resources, from textual as in most of modern search engines, machines. So, while text itself is already efficaciously to multimedia. The idea of “anchor” as information unit is used as knowledge representation for machines, digital here introduced to view resources from different perspectives multimedia resources like images and videos cannot in and to access existing resources and metadata archives. general be used as they are for efficient classification and Moreover, the platform uses an ontology as a conceptual retrieval. Some intensive processing or manual metadata representation of a well-defined domain in order to creation is necessary to extract and associate semantic semantically classify and retrieve anchors (and the related information to a given multimedia resource. resources). Specifically, the architecture of the proposed platform aims at being as modular and easily extensible as In this context, the proposed work aims at providing a possible, in order to permit the inclusion of state-of-the-art flexible, lightweight and ready-to-use platform for the techniques for the classification and retrieval of multimedia semantic classification, search and retrieval of resources. -
GATEKEEPER Platform Overview
GATEKEEPER – Platform overview Table of contents ABSTRACT .........................................................................................................................................................4 1 ARCHITECTURE DEFINITION PRINCIPLES ................................................................................... 5 1.1 WEB OF THINGS ................................................................................................................................................................. 5 1.1.1 Principles for Gatekeeper data ....................................................................................................................... 6 1.1.2 Gatekeeper Web of Thing based architecture .................................................................................... 7 1.1.3 Role of WoT Thing Description ....................................................................................................................... 9 1.1.4 Role of FHIR and relation with Thing Description ............................................................................ 15 1.2 GATEKEEPER PLATFORM STAKEHOLDERS ........................................................................................................ 16 1.3 SECURITY AND PRIVACY CONSIDERATIONS ....................................................................................................... 17 1.3.1 Infrastructure security ..........................................................................................................................................18 -
Semantic Computing
SEMANTIC COMPUTING 10651_9789813227910_TP.indd 1 24/7/17 1:49 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence ISSN: 2529-7686 Published Vol. 1 Semantic Computing edited by Phillip C.-Y. Sheu 10651 - Semantic Computing.indd 1 27-07-17 5:07:03 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence – Vol. 1 SEMANTIC COMPUTING Editor Phillip C-Y Sheu University of California, Irvine World Scientific NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TAIPEI • CHENNAI • TOKYO 10651_9789813227910_TP.indd 2 24/7/17 1:49 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence ISSN: 2529-7686 Published Vol. 1 Semantic Computing edited by Phillip C.-Y. Sheu Catherine-D-Ong - 10651 - Semantic Computing.indd 1 22-08-17 1:34:22 PM Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE Library of Congress Cataloging-in-Publication Data Names: Sheu, Phillip C.-Y., editor. Title: Semantic computing / editor, Phillip C-Y Sheu, University of California, Irvine. Other titles: Semantic computing (World Scientific (Firm)) Description: Hackensack, New Jersey : World Scientific, 2017. | Series: World Scientific encyclopedia with semantic computing and robotic intelligence ; vol. 1 | Includes bibliographical references and index. Identifiers: LCCN 2017032765| ISBN 9789813227910 (hardcover : alk. paper) | ISBN 9813227915 (hardcover : alk. paper) Subjects: LCSH: Semantic computing. Classification: LCC QA76.5913 .S46 2017 | DDC 006--dc23 LC record available at https://lccn.loc.gov/2017032765 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. -
D2.9 Dissemination Plan Version C
Ref. Ares(2019)2902574 - 30/04/2019 C3-Cloud “A Federated Collaborative Care Cure Cloud Architecture for Addressing the Needs of Multi-morbidity and Managing Poly-pharmacy” PRIORITY Objective H2020-PHC-25-2015 - Advanced ICT systems and services for integrated care D2.9 Dissemination Plan version c Work Package: WP2 Dissemination, Exploitation and Innovation Related Activities” Due Date: 30 April 2019 Actual Submission Date: 30 April 2019 Project Dates: Project Start Date: 01 May 2016 Project End Date: 30 April 2020 Project Duration: 48 months Deliverable Leader: EuroRec Project funded by the European Commission within the Horizon 2020 Programme (2014-2020) Dissemination Level PU Public CO Confidential, only for members of the consortium (including the Commission Services) X EU-RES Classified Information: RESTREINT UE (Commission Decision 2005/444/EC) EU-CON Classified Information: CONFIDENTIEL UE (Commission Decision 2005/444/EC) EU-SEC Classified Information: SECRET UE (Commission Decision 2005/444/EC) Document History: Version Date Changes From Review V0.1 20-04-2019 Initial document, most of content EuroRec - V0.2 27-04-2019 Further partner inputs plus web site EuroRec All screenshots V0.3 29-04-2019 Further review and addition of new WARWICK - material V1.0 30-04-2019 Final checks and editing by the WARWICK Coordinating team Contributors Geert Thienpont (EuroRec), Sarah N. Lim Choi Keung (WARWICK), (Beneficiary) Theodoros N. Arvanitis (WARWICK), George Despotou (WARWICK), Marie Sherman (RJH), Marie Beach (SWFT), Veli Stroetmann (empirica), Malte von Tottleben (empirica), Gokce Banu Laleci Erturkmen (SRDC), Mustafa Yuksel (SRDC), Göran Ekestubbe (CAMBIO), Mattias Fendukly (CAMBIO), Pontus Lindman (MEDIXINE), Dolores Verdoy (KG/OSAKI), Esteban de Manuel Keenoy (KG/OSAKI), Lamine Traore (INSERM), Marie- Christine Jaulent (INSERM) Responsible Author Dipak Kalra Email [email protected] Beneficiary EuroRec D2.9 Version 1.0, dated 30 April 2019 Page 2 of 71 TABLE OF CONTENTS 1. -
Oracle White Paper May 19Th, 2015
An Oracle White Paper May 19th, 2015 Oracle Metadata Management v12.1.3.0.2 New Features Overview Oracle Metadata Management version 12.1.3.0.2 – May 19th, 2015 New Features Overview Disclaimer This document is for informational purposes. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described in this document remains at the sole discretion of Oracle. This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. This document and information contained herein may not be disclosed, copied, reproduced, or distributed to anyone outside Oracle without prior written consent of Oracle. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with Oracle or its subsidiaries or affiliates. 1 Oracle Metadata Management version 12.1.3.0.2 – May 19th, 2015 New Features Overview Table of Contents Executive Overview ............................................................................ 3 Oracle Metadata Management 12.1.3.0.2 .......................................... 4 Data Model Diagram Visualizer ...................................................... 4 HTML5 redesign ..................................................................................... 4 New interactive search ........................................................................... 5 New diagram auto -
Emergent Computing Joint ERCIM Actions: ‘Beyond the Horizon’ Anticipating Future and Emerging Information Society Technologies
European Research Consortium for Informatics and Mathematics Number 64, January 2006 www.ercim.org Special: Emergent Computing Joint ERCIM Actions: ‘Beyond the Horizon’ Anticipating Future and Emerging Information Society Technologies European Scene: Routes to Open Access Publishing CONTENTS JOINT ERCIM ACTIONS THE EUROPEAN SCENE 4 Fourth ERCIM Soft Computing Workshop The Routes to Open Access by Petr Hajek, Institute of Computer Science, Academy of 16 Open Access: An Introduction Sciences / CRCIM, Czech Republic by Keith G Jeffery, Director IT, CCLRC and ERCIM president 4 Cor Baayen Award 2006 18 Publish or Perish — Self-Archive to Flourish: The Green Route to Open Access 5 Second ERCIM Workshop ‘Rapid Integration of Software by Stevan Harnad, University of Southampton, UK Engineering Techniques’ by Nicolas Guelfi, University of Luxembourg 19 The Golden Route to Open Access by Jan Velterop 5 Grid@Asia: European-Asian Cooperation Director of Open Access, Springer in Grid Research and Technology by Bruno Le Dantec , ERCIM Office 20 ERCIM Statement on Open Access 6 GFMICS 2005 — 10th International Workshop on Formal 21 Managing Licenses in an Open Access Community Methods for Industrial Critical Systems by Renato Iannella National ICT Australia by Mieke Massink and Tiziana Margaria 22 W3C at the Forefront of Open Access Beyond-The-Horizon Project by Rigo Wenning, W3C 7 Bits, Atoms and Genes Beyond the Horizon 23 Cream of Science by Dimitris Plexousakis, ICS-FORTH, Greece by Wouter Mettrop, CWI, The Netherlands 8 Thematic Group 1: Pervasive Computing and Communications SPECIAL THEME: by Alois Ferscha, University of Linz, Austria EMERGENT COMPUTING 24 Introduction to the Special Theme 9 Thematic Group 2: by Heather J. -
Semantic Web OWL RDF and SPARQL
Searching The Semantic Web Lecturer: Kyumars Sheykh Esmaili Semantic Web Research Laboratory Computer Engineering Department Sharif University of Technology Fall 2005 Table of Content Introduction Semantic web Search Engines Ontology Search Engines Meta Ontology Search Engines Crawler Based Ontology Search Engines Semantic Search Engines Context Based Search Engines Semantic Annotation Evolutionary Search Engines Semantic Association Discovery Engines Discussion and Evaluation References Semantic Web Research LaboratorySearching The Semantic Web Sharif University of Technology 2 Table of Content Introduction Semantic web Search Engines Ontology Search Engines Meta Ontology Search Engines Crawler Based Ontology Search Engines Semantic Search Engines Context Based Search Engines Semantic Annotation Evolutionary Search Engines Semantic Association Discovery Engines Discussion and Evaluation References Semantic Web Research LaboratorySearching The Semantic Web Sharif University of Technology 3 Before and After ? Semantic Web Research LaboratorySearching The Semantic Web Sharif University of Technology 4 Semantic Web Terminology A Term is a non-anonymous RDF resource which is the URI reference of either a class or a property. rdfs:Class foaf:Person An Individual refers to a non-anonymous RDF resource which is the URI reference of a class member. foaf:Person http://.../foaf.rdf#finin An Ontology contains mostly term definition (i.e. classes and properties). It corresponds to T-Box in Description Logic. An Annotation contains mostly class -
A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation
sensors Article A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation Ezequiel Simeoni 1,* , Eugenio Gaeta 1 , Rebeca I. García-Betances 1 , Dave Raggett 2, Alejandro M. Medrano-Gil 1 , Diego F. Carvajal-Flores 1 , Giuseppe Fico 1 , María Fernanda Cabrera-Umpiérrez 1 and María Teresa Arredondo Waldmeyer 1 1 Life Supporting Technologies (LifeSTech), ETSI Telecomunicaciones Universidad Politécnica de Madrid, Av. Complutense s/n, 28040 Madrid, Spain; [email protected] (E.G.); [email protected] (R.I.G.-B.); [email protected] (A.M.M.-G.); [email protected] (D.F.C.-F.); gfi[email protected] (G.F.); [email protected] (M.F.C.-U.); [email protected] (M.T.A.W.) 2 W3C/ERCIM, 2004, Route des Lucioles, Sophia Antipolis, 06410 Biot, France; [email protected] * Correspondence: [email protected] Abstract: Internet of Things (IoT) technologies are already playing an important role in our daily activities as we use them and rely on them to increase our abilities, connectivity, productivity and quality of life. However, there are still obstacles to achieving a unique interface able to transfer full control to users given the diversity of protocols, properties and specifications in the varied IoT ecosystem. Particularly for the case of home automation systems, there is a high degree of fragmentation that limits interoperability, increasing the complexity and costs of developments Citation: Simeoni, E.; Gaeta, E.; and holding back their real potential of positively impacting users. In this article, we propose García-Betances, R.I.; Raggett, D.; implementing W3C’s Web of Things Standard supported by home automation ontologies, such as Medrano-Gil A.M.; Carvajal-Flores SAREF and UniversAAL, to deploy the Living Lab Gateway that allows users to consume all IoT D.F.; Fico, G.; Cabrera-Umpiérrez, devices from a smart home, including those physically wired and using KNX® technology. -
Sequential Behavioral Modeling for Scalable Iot Devices and Systems
Sequential Behavioral Modeling for Scalable IoT Devices and Systems Ege Korkan1, Sebastian Kaebisch2, Matthias Kovatsch2, Sebastian Steinhorst1 1 Technical University of Munich, Germany, Email: fege.korkan, [email protected] 2 Siemens AG, Germany, Email: fsebastian.kaebisch, [email protected] Abstract—The Internet of Things (IoT) enables connectivity be- tween devices, thereby allowing them to interact with each other. A recurring problem is the emergence of siloed IoT platforms due to proprietary standards. Recently, the World Wide Web Consortium (W3C) proposed a human-readable and machine- System understandable format called Thing Description (TD). It allows to uniformly describe device and service interfaces of different IoT TD 2 TD 2 4 standards with syntactic and semantic information, and hence 1 3 Thing A Thing B 1 3 enables semantic interoperability. However, describing sequential behavior of devices, which is essential for many cyber-physical systems, is not covered. In this paper, we propose a systematic X TD Contents: asd way to describe such sequential behavior as an extension within Possible TD Identification TDs, thereby increasing their semantic expressiveness through Interaction: Thing C possible, valid state transitions. This enables safe and desired asda Interaction List operation of devices as well as scalability by modeling systems - Property Data Type as sequential compositions of Things. We show in a case study - Action 1 Data Access that previously unmodelable behavior can now be expressed and - Event TD Protocols the overall manual intervention requirements of state-of-the-art Security implementations can be significantly reduced. Figure 1: An abstracted view of an IoT System with 3 IoT Devices each with Index Terms—Internet of Things, Thing Description, CPS, an associated Thing Description (TD). -
Semantic Interoperability in Internet of Things
CORE Metadata, citation and similar papers at core.ac.uk Provided by TUT DPub SYED SAFDAR ALI SHAH SEMANTIC INTEROPERABILITY IN INTERNET OF THINGS Master of Science thesis Examiner: Prof. Kari Systä Examiner and topic approved by the Dean of the Faculty of Computing and Electrical Engineering on date 29.03.2017 i TABLE OF CONTENTS 1. Introduction . 1 2. Internet of Things . 3 2.1 Definition of the Internet of Things . 3 2.2 Internet of Things Technologies . 4 2.2.1 Network/Link Layer . 6 2.2.2 Internet Layer . 6 2.2.3 Transport Layer . 7 2.2.4 Data Protocols . 8 2.2.5 Discovery . 9 2.2.6 Device Management . 10 2.2.7 Semantic . 11 3. Interoperability in the Internet of Things . 14 3.1 Technical Interoperability . 14 3.2 Syntactic Interoperability . 15 3.3 Semantic Interoperability . 15 3.3.1 Proxy Gateway . 16 3.3.2 Unified Data Models and Frameworks . 16 3.3.3 Ontologies . 16 4. Proposed Semantic Interoperability Solution for IoT . 18 4.1 Endpoint . 19 4.2 Resource Directory . 20 4.3 Interoperability Server . 21 4.3.1 Apache Jena . 21 4.3.2 Thing Description Repository . 22 4.3.3 Semantic Engine . 24 ii 4.3.4 Management Client . 26 4.4 Interfaces . 26 4.4.1 Peer Interface . 27 4.4.2 Resource Directory Interface . 27 4.4.3 Interoperability Server Interface . 30 4.4.4 Management Interface . 32 4.5 Working Principles . 36 4.5.1 Temperature Sensor, Fan Actuator, and Central Controller reg- isters their Thing Descriptions with Interoperability Server .