DOCSLIB.ORG

Semantics Driven Agent Programming

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Semantics Driven Agent Programming ALMA MATER STUDIORUM - UNIVERSITÀ DI BOLOGNA DOTTORATO DI RICERCA IN: Computer Science and Engineering Ciclo XXXII Settore Concorsuale: 09/H1 Settore Scientifico Disciplinare: ING-INF/05 SEMANTICS DRIVEN AGENT PROGRAMMING Presentata da: Francesco Antoniazzi Coordinatore Dottorato Supervisore Prof. Davide Sangiorgi Prof. Tullio Salmon Cinotti Co-Supervisore Prof. Luciano Bononi Esame finale anno 2020 This work is licensed under a Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” license. francesco.antoniazziunibo.it francesco.antoniazzioutlook.com Think green before printing this Thesis Contents Abstract in English 5 Abstract in Italiano 7 Abstract en Français 9 Introduction 11 1 Background Research 15 1.1 Internet of Things ............................... 15 1.2 The Semantic Web ............................... 19 1.2.1 Visualizing the Semantic Web ..................... 21 1.2.2 AudioCommons Project ........................ 34 1.3 SPARQL Event Processing Architecture ................... 37 1.3.1 Origins ................................. 37 1.3.2 Architecture .............................. 38 1.3.3 Future .................................. 40 2 Semantic Internet of Things 43 2.1 Semantic Interoperability ........................... 43 2.2 Internet of Musical Things ........................... 45 2.2.1 Methodology, audience, and scope .................. 47 2.2.2 Related ontologies and data models ................. 48 2.2.3 Specification .............................. 49 2.2.4 Ontology description .......................... 51 2.2.5 Implementation and maintenance ................... 58 2.2.6 Evaluation ............................... 59 3 Semantic Web of Things 67 3.1 W3C Web of Things vision .......................... 67 3.2 A Dynamic Ontology for the Semantic Web of Things ........... 69 3.2.1 Related Work .............................. 70 3.2.2 Semantic Web Things ......................... 75 3 3.2.3 Interaction Patterns: the PAE paradigm ............... 76 3.2.4 DataSchema and FieldSchema .................... 82 4 Semantic Driven Agent Programming 91 4.1 Related Works ................................. 91 4.2 SWOT agents framework and Evaluation .................. 93 4.2.1 Cocktail framework .......................... 93 4.2.2 Cocktail: in-use analysis ........................ 94 4.2.3 Evaluation ............................... 97 4.3 Next Steps ................................... 100 4.3.1 Cocktail example ............................ 101 4.3.2 Habitat project example ........................ 104 4.3.3 Future directions ............................ 105 Conclusion 109 List of Ontologies & Prefixes 113 List of Figures 115 List of Tables 118 Bibliography 121 4 Abstract in English n the last two decades the Information Technology changed substantially the life of I people all around the World. Just a few years ago, for instance, paper support was needed to exchange all kind of data, while now electronics is indeed the main instrument of communication. This mutation was originally due mostly to the efficiency, while now it is, hopefully, also due to an increased attention towards environmental issues. Information and data have proved over the time the importance of their role, con- tributing to a plethora of applications that allow the physical world to interact with mankind by the means of services dispatched pervasively and freely accessible. The Internet is the kernel of such complex setup that is called Internet of Things (IoT). The IoT inherited from the Internet a chaotic interface. Protocols, conventions, mechanisms are different from an application to the other, and it is difficult and expensive to discover and make applications compatible with one another. From this consideration two exceptional ideas were born, namely the Semantic Web and the Web of Things (WoT). The latter would unify the IoT on an application level shared view, enabling standard discovery mechanisms and definitions. The former, on the other hand, intents to provide the tools to formalize the knowledge contents of the World Wide Web in a simultaneously human and machine understandable way. This Thesis aims to explore both these two concepts and merge them into the Se- mantic Web of Things using the best of each. Therefore we hereby propose, describe, evaluate and use two ontologies: the Internet of Musical Things ontology, aiming to outline a semantic description of IoT; and a Semantic WoT ontology, aiming to push further the state of the art of IoT unification and standardization through a dynamic semantic approach. 5 6 Abstract in Italiano egli ultimi due decenni le nuove Tecnologie dell’Informazione hanno cambiato N radicalmente la vita delle persone in tutto il mondo. Soltanto qualche anno fa, per esempio, lo scambio di informazione era necessariamente effettuato sotto forma cartacea in quasi ogni ambito. Oggi, invece, il mezzo elettronico viene privilegiato sempre più per questioni di efficienza nonché, recentemente, si spera anche per motivi legati alla sostenibilità ambientale. L’informazione ha dato prova, nel corso del tempo, della sua importanza. Ha contri- buito a rendere possibili numerosissime applicazioni in grado di far interagire l’umanità con il mondo fisico attraverso un’astrazione composta da servizi facilmente accessibili e distribuiti ovunque. Internet è il cuore di questo grande sistema chiamato Internet of Things (IoT). L’IoT ha in comune con Internet la sua interfaccia caotica e la mancanza di ordine. I protocolli, le convenzioni, i meccanismi cambiano da una applicazione all’altra, rendendo difficile e costoso scoprire e creare sistemi compatibili. Da queste considerazioni ormai accettate dalla comunità traggono origine due concetti eccezionali: il Semantic Web e il Web of Things (WoT). Quest’ultimo ha come fine quello di unificare l’IoT ad un livello applicativo condiviso rendendo disponibili definizioni e meccanismi standard per la scoperta dei dispositivi. Il primo, invece, fornisce degli strumenti per formalizzare la conoscenza distribuita nel World Wide Web in modo che sia contemporanemante fruibile all’uomo e alle macchine. Questa Tesi si accinge ad esplorare i due concetti appena descritti, ed a riunirli usan- do il meglio di entrambi nel Semantic Web Of Things. Per fare ciò si proporranno, descriveranno, valuteranno ed useranno due ontologie: l’ontologia dell’Internet of Mu- sical Things, che servirà per mostrare una definizione semantica dell’IoT; e l’ontologia del Semantic WoT, il cui scopo è di spingere oltre lo Stato dell’Arte nell’unificazione dell’IoT e nella sua standardizzazione attraverso un approccio semantico e dinamico. 7 8 Abstract en Français es deux dernières décennies ont vu les nouvelles Technologies de l’Information L changer de manière radicale la vie des gens partout dans le monde. Il n’y a que quelques années, par exemple, des supports en papier étaient nécessaires pour l’échange des données, alors qu’à présent l’instrument principal est l’électronique. Ce changement était dû à l’ origine à l’efficacité de la communication. Maintenant, on l’espère, la raison est aussi liée à la tutelle de l’environnement. Il a été largement démontré que l’information joue un rôle essentiel : innombrables applications ont été développées pour connecter le monde physique et l’humanité à tra- vers des services distribués partout et librement accessibles. Internet est au centre de toute cette infrastructure, qui n’est autre que l’Internet des Objets (IoT). L’IoT et Internet ont en commun leur organisation chaotique. Les protocoles, les conventions, les fonctionnements internes peuvent être très différents d’une application à l’autre : il est souvent difficile et coûteux de découvrir et créer des applications com- patibles avec le reste des systèmes qui sont à disposition. Ce concept est à l’origine de deux idées exceptionnelles : le Web Sémantique, et le Web des Objets (WoT). Celui-ci a pour but d’unifier l’IoT à un niveau applicatif commun avec des mécanismes de dé- couverte et un vocabulaire standard. Le premier, d’autre part, propose les instruments pour mettre de l’ordre dans la connaissance du World Wide Web, de façon à la rendre à la fois compréhensible à l’être humain, et aux machines. Cette Thèse explore donc les deux idées à peine présentées, et additionne leurs meilleures qualités pour obtenir le Web des Objets Sémantiques. Ainsi sont proposées, décrites, évaluées et utilisées deux ontologies : celle de l’Internet des Objets Musicaux, pour produire une description sémantique de l’IoT ; et celle du WoT Sémantique, qui voudrait avancer l’état de l’art de la recherche sur l’unification de l’IoT de manière sémantique et dynamique. 9 10 Introduction emantic Driven Agent Programming idea joins together concepts that are relatively S well-known in literature. Agent programming, as it will be discussed, dates back to the early 90’s [1], while the Semantic Web was introduced by Tim Berners Lee in 2001 [2]. The innovation proposed by this Thesis, therefore, is not given by those concepts taken on their own, but is rather the outcome of their integration into several ideas and projects, which are going to be explored in the following Chapters. The effort made to define such collaboration targets the third pole of interest of the Thesis, namely the Internet of Things (IoT) [3]. As a matter of fact, the IoT represents one of the most outstanding global creativity sources of the last century. With the advent of affordable computing, pervasive electronics and the Internet, technology started to follow a quick and exponential
Load more

Recommended publications
  • FI-WARE User and Programmers Guide WP6 Front Page 1 FI-WARE User and Programmers Guide WP6 Front Page
    FI-WARE User and Programmers Guide WP6 front page 1 FI-WARE User and Programmers Guide WP6 front page Large-scale Integrated Project (IP) D.6.4.a: User and Programmers Guide Project acronym: FI-WARE Project full title: Future Internet Core Platform Contract No.: 285248 Strategic Objective: FI.ICT-2011.1.7 Technology foundation: Future Internet Core Platform Project Document Number: ICT-2011-FI-285248-WP6-D6.4a Project Document Date: 30 June 2012 Deliverable Type and Security: Public Author: FI-WARE Consortium Contributors: FI-WARE Consortium Abstract: This deliverable contains the User and Programmers Guide for the Generic Enablers of Data/Context Management chapter, being included in the First FI-WARE release. Keyword list: FI-WARE, Generic Enabler, Bigdata, Context, Events, Semantic Web, Multimedia. Contents BigData Analysis - User and Programmer Guide 2 CEP - User and Programmer Guide 89 Location Platform - User and Programmer Guide 90 Multimedia Analysis - User and Programmer Guide 95 Query Broker - User and Programmer Guide 105 Semantic Annotation - Users and Programmers Guide 110 Semantic Application Support - Users and Programmers Guide 113 BigData Analysis - User and Programmer Guide 2 BigData Analysis - User and Programmer Guide Introduction This guide covers the user and development aspects of the SAMSON platform, version 0.6.1. The SAMSON platform has been designed for the processing of large amounts of data, in continuous mode (streaming), distributing tasks in a medium-size cluster of computers, following the MapReduce paradigm Jeffrey Dean and Sanjay Ghemawat. “MapReduce: Simplified data processing on large clusters” [1]. The platform provides the necessary framework to allow a developer to focus on solving analytical problems without needing to know how distribute jobs and data, and their synchronization.
    [Show full text]
  • 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
    [Show full text]
  • A Question Answering System for Chemistry
    A Question Answering System for Chemistry Preprint Cambridge Centre for Computational Chemical Engineering ISSN 1473 – 4273 A Question Answering System for Chemistry Xiaochi Zhou1, Daniel Nurkowski4, Sebastian Mosbach1;2, Jethro Akroyd1;2, Markus Kraft1;2;3 released: January 25, 2021 1 Department of Chemical Engineering 2 CARES and Biotechnology Cambridge Centre for Advanced University of Cambridge Research and Education in Singapore Philippa Fawcett Drive 1 Create Way Cambridge, CB3 0AS CREATE Tower, #05-05 United Kingdom Singapore, 138602 3 School of Chemical 4 CMCL Innovations and Biomedical Engineering Sheraton House Nanyang Technological University Castle Park, Castle Street 62 Nanyang Drive Cambridge, CB3 0AX Singapore, 637459 United Kingdom Preprint No. 266 Keywords: Question Answering system, Natural language processing, Knowledge Graph Edited by Computational Modelling Group Department of Chemical Engineering and Biotechnology University of Cambridge Philippa Fawcett Drive Cambridge, CB3 0AS United Kingdom CoMo E-Mail: [email protected] GROUP World Wide Web: https://como.ceb.cam.ac.uk/ Abstract This paper describes the implementation and evaluation of a proof-of-concept Ques- tion Answering system for accessing chemical data from knowledge graphs which offer data from chemical kinetics to chemical and physical properties of species. We trained a question type classification model and an entity extraction model to interpret chemistry questions of interest. The system has a novel design which applies a topic model to identify the question-to-ontology affiliation. The topic model helps the sys- tem to provide more accurate answers. A new method that automatically generates training questions from ontologies is also implemented. The question set generated for training contains 80085 questions under 8 types.
    [Show full text]
  • Discussion #1 | University of Texas at Austin | August 13, 2018 Facilitated By: Itza A
    Introduction to Linked Data Discussion #1 | University of Texas at Austin | August 13, 2018 Facilitated by: Itza A. Carbajal, LLILAS Benson Latin American Metadata Librarian Hello! My name is Itza A. Carbajal I will be facilitating this discussion series on Linked Data I am the Latin American Metadata Librarian for a Post Custodial project at LLILAS Benson Have questions? Email me at: [email protected] Like twitter? You can find me at: @archiviststan Housekeeping ◎ Discussions are meant to highlight collective wisdom of the group ◎ Attendance to all discussion meetings not required, but recommended ◎ Take home practices are not required, but encouraged to further an individual’s understanding ◎ Readings are not required, but should be considered as a method for self education or for sharing with others Link to LIVE syllabus: http://bit.ly/SYLLABUSUTLD Link to reading materials: http://bit.ly/READUTLD 1. Discussion #1 Topics Topics to Discuss ◎ Semantic Web ◎ Linked data principles ◎ RDF and Triple statements Related Topics not covered in discussions ◎ Linked Open Data ◎ Examples of linked open data sets ◎ Linked Data platform 2. First, the Semantic Web Semantic Web (project) ◎ Derives from the concept of semantics defined as the study of meanings ◎ Extension to the current World Wide Web ◎ Also known as Web 3.0 where the web can now “read-write-execute” ◎ Changes the current web of information to a web of data including data inside the web and outside ◎ Core functions include semantic markup ○ Semantic markup - data interchange formats accessible to humans and machine ◎ Focuses on adding meaning/context to information giving machines and humans the ability to communicate and cooperate ◎ Relies on machine-readable metadata to expresses that meaning/context ◎ No formal definition, still ongoing and constantly maturing 3.
    [Show full text]
  • Constructing Reference Semantic Predictions from Biomedical Knowledge Sources
    Constructing Reference Semantic Predictions from Biomedical Knowledge Sources Demeke Ayele1, J. P. Chevallet2, Million Meshesha1, Getnet Kassie1 (1) Addis Ababa University, Addis Ababa, Ethiopia (2) University of Grenoble, Grenoble, France {demekeayele, meshe8, getnetmk}@gmail.com, jean- [email protected] ABSTRACT Semantic tuples are core component of text mining and knowledge extraction systems in biomedicine. The practical success of these systems significantly depends on the correctness and quality of the extracted semantic tuples. The quality and correctness of the semantic predictions can be measured against a benchmark semantic structure. In this article, we presented an approach for constructing a reference semantic tuple structure based on the existing biomedical knowledge sources in which the evaluation is based on the UMLS knowledge sources. In the evaluation, 7400 semantic triples are extracted from UMLS knowledge sources and the semantic predictions are constructed using the proposed approach. In the semantic triples, 87 concepts are found redundantly classified and 207 pair of semantic triples showed hierarchically inconsistent. 128 are found to be non-taxonomically inconsistent. The quality of the semantic triple is also judged using expert evaluators. The Cohen's kappa coefficient is used to measure the degree of agreement between two evaluators and the result is promising (0.9). Construire des prévisions de référence sémantique à partir de sources de connaissances biomédicales Les "tuples sémantiques" forment un élément essentiel à la fouille de texte et aux systèmes d'extraction de connaissances dans le domaine biomédical. Le succès en pratique des systèmes exploitant ces informations sémantique, dépend fortement de l'exactitude et de la qualité des tuples sémantiques.
    [Show full text]
  • Distributed Semantic Sensor Networks How to Use Semantics and Knowledge Distribution to Integrate Sensor Data of Disparate Data Sources
    2007 Distributed Semantic Sensor Networks How to use semantics and knowledge distribution to integrate sensor data of disparate data sources. In this research project we focused on sensor networks and how semantic web technologies and knowledge sharing can make integration of distributed sensor data possible. To achieve this we have first identified the main challenges to address to allow for data integration. A distributed semantic sensor network framework is proposed that uses semantic web techniques and knowledge sharing to address these challenges. We propose that knowledge sharing in a sensor network is a key aspect of data integration in a dynamic environment, since it allows the network to handle changes in the environment. This project is innovative in that it proposes new ways to handle semantic integration in a distributed environment, by using question federation and data conversion on semantically annotated data and questions. It contributes to current research in that our framework enables data integration of distributed sensor data. Masters Student M.J. van der Veen, Department of Artificial Intelligence, Rijksuniversiteit Groningen, Groningen Supervisors Bart Verheij, Department of Artificial Intelligence, Rijksuniversiteit Groningen Arnoud de Jong, TNO ICT & Telecommunicatie, Groningen 1 People A masters student at the Department of Artificial Intelligence at the Rijksuniversiteit Groningen in The Netherlands. This thesis is the final work in his masters studies. His main interests besides writing this thesis is doing sports, coaching, travelling and making music . Masters Student: Maarten van der Veen A tenured lecturer/researcher (in Dutch: universitair docent) at the University of Groningen, Department of Artificial Intelligence and a member of the ALICE institute.
    [Show full text]
  • Applying the Semantic Web to Computational Chemistry
    Applying the Semantic Web to Computational Chemistry Neil S. Ostlund, Mirek Sopek Chemical Semantics Inc. , Gainesville, Florida, USA {ostlund, sopek}@chemicalsemantics.com Abstract. Chemical Semantics is a new start-up devoted to bringing the Semantic Web to computational chemistry, with a future goal to cover chemical results of other kinds, including experimental. We have created a prototype test bed that enables computational chemists to publish the results of their computations (for example: structure, energies and wave functions of Ab Initio calculations) on servers (powered by semantic triple stores) holding RDF data. In addition, scientists will be able to search across results produced by themselves and other researchers using SPARQL queries and faceted search built on top of it. The semantics of computational chemistry oriented RDF data is defined by an ontology identified as “GC” (Gainesville Core). Gainesville Core defines concepts such as: theoretical models used in computations, molecular systems (as collections of atoms and molecules), molecular arrangements which describe system evolution in time or in phase space and so on. The poster demonstrates the project during its early stage, including a description and demonstration of the prototype portal created by Chemical Semantics. This paper is the concise description of the poster content. Keywords: computational chemistry, semantic web, linked data, Gainesville Core, ontology Chemical Semantics portal main targets The Chemical Semantic portal, now in its prototype version, has the following long term goals: 1. Interoperable PUBLISHING of Computational Chemistry calculations using Linked Data principles 2. Enhanced search across all published results with basic reasoning enabled by the new ontology 3. FEDERATION of published data with existing web-based chemical datasets 4.
    [Show full text]
  • Relext: Relation Extraction Using Deep Learning Approaches for Cybersecurity Knowledge Graph Improvement
    RelExt: Relation Extraction using Deep Learning approaches for Cybersecurity Knowledge Graph Improvement Aditya Pingle, Aritran Piplai, Sudip Mittal, Anupam Joshi James Holt, and Richard Zak University of Maryland, Baltimore County, Baltimore, MD 21250, USA Laboratory for Physical Sciences fadiping1, apiplai1, smittal1, [email protected] fholt, [email protected] Abstract—Security Analysts that work in a ‘Security Opera- cybersecurity reports, CVE [21], CWE [22], National Vul- tions Center’ (SoC) play a major role in ensuring the security nerability Datasets [28], and any cybersecurity text publicly of the organization. The amount of background knowledge they available. Various SIEM systems, fetch, process, and store have about the evolving and new attacks makes a significant difference in their ability to detect attacks. Open source threat much of the cyber threat intelligence available through OSINT intelligence sources, like text descriptions about cyber-attacks, sources. Knowledge Graphs (KG) specifically to store cyber can be stored in a structured fashion in a cybersecurity knowl- threat intelligence has been used by many cybersecurity in- edge graph. A cybersecurity knowledge graph can be paramount formatics systems. These cybersecurity knowledge graphs can in aiding a security analyst to detect cyber threats because it not only store but are also be able to retrieve data and answer stores a vast range of cyber threat information in the form of semantic triples which can be queried. A semantic triple complex queries asked by the security analysts. contains two cybersecurity entities with a relationship between The dependence of various cybersecurity informatics sys- them. In this work, we propose a system to create semantic tems on various knowledge representation schemes makes triples over cybersecurity text, using deep learning approaches it imperative that we develop systems that improve these to extract possible relationships.
    [Show full text]
  • FI-WARE Product Vision Front Page Ref
    FI-WARE Product Vision front page Ref. Ares(2011)1227415 - 17/11/20111 FI-WARE Product Vision front page Large-scale Integrated Project (IP) D2.2: FI-WARE High-level Description. Project acronym: FI-WARE Project full title: Future Internet Core Platform Contract No.: 285248 Strategic Objective: FI.ICT-2011.1.7 Technology foundation: Future Internet Core Platform Project Document Number: ICT-2011-FI-285248-WP2-D2.2b Project Document Date: 15 Nov. 2011 Deliverable Type and Security: Public Author: FI-WARE Consortium Contributors: FI-WARE Consortium. Abstract: This deliverable provides a high-level description of FI-WARE which can help to understand its functional scope and approach towards materialization until a first release of the FI-WARE Architecture is officially released. Keyword list: FI-WARE, PPP, Future Internet Core Platform/Technology Foundation, Cloud, Service Delivery, Future Networks, Internet of Things, Internet of Services, Open APIs Contents Articles FI-WARE Product Vision front page 1 FI-WARE Product Vision 2 Overall FI-WARE Vision 3 FI-WARE Cloud Hosting 13 FI-WARE Data/Context Management 43 FI-WARE Internet of Things (IoT) Services Enablement 94 FI-WARE Applications/Services Ecosystem and Delivery Framework 117 FI-WARE Security 161 FI-WARE Interface to Networks and Devices (I2ND) 186 Materializing Cloud Hosting in FI-WARE 217 Crowbar 224 XCAT 225 OpenStack Nova 226 System Pools 227 ISAAC 228 RESERVOIR 229 Trusted Compute Pools 230 Open Cloud Computing Interface (OCCI) 231 OpenStack Glance 232 OpenStack Quantum 233 Open
    [Show full text]
  • Thinking Outside the Tbox
    Thinking Outside the TBox Multiparty Service Matchmaking as Information Retrieval David J. Lambert School of Informatics University of Edinburgh I V N E R U S E I T H Y T O H F G E R D I N B U Doctor of Philosophy Centre for Intelligent Systems and their Applications School of Informatics University of Edinburgh 2009 Abstract Service oriented computing is crucial to a large and growing number of computational undertakings. Central to its approach are the open and network-accessible services provided by many different organisations, and which in turn enable the easy creation of composite workflows. This leads to an environment containing many thousands of services, in which a programmer or automated composition system must discover and select services appropriate for the task at hand. This discovery and selection process is known as matchmaking. Prior work in the field has conceived the problem as one of sufficiently describing individual services using formal, symbolic knowledge representation languages. We review the prior work, and present arguments for why it is optimistic to assume that this approach will be adequate by itself. With these issues in mind, we examine how, by reformulating the task and giving the matchmaker a record of prior service performance, we can alleviate some of the problems. Using two formalisms—the incidence calculus and the lightweight coordination calculus—along with algorithms inspired by information retrieval techniques, we evolve a series of simple matchmaking agents that learn from experience how to select those services which performed well in the past, while making minimal demands on the service users.
    [Show full text]
  • An Approach for Knowledge Graph Construction from Spanish Texts
    ISSN 1870-4069 An Approach for Knowledge Graph Construction from Spanish Texts Andrea G. Garcia Perez1, Ana B. Rios Alvarado1, Tania Y. Guerrero Melendez1, Edgar Tello Leal1, Jose L. Martinez Rodriguez2 1 Autonomous University of Tamaulipas, Mexico 2 CINVESTAV Unidad Tamaulipas, Mexico [email protected], farios, tyguerre, [email protected], [email protected] Abstract. Knowledge Graphs (KGs) represent valuable data sources for the Educational and Learning field, allowing computers and peo- ple to process and interpret information in an easier way. In addition KGs are useful to get information by software systems on any data re- source (person, place, organization, among others). KGs are represented through triples composed of entities and semantic relations commonly obtained from textual resources. However, exploiting triples from text is complicated due to linguistic variations, where Spanish has been slightly approached. This paper presents a method for constructing KGs from textual resources in Spanish. The method is composed of four stages: 1) obtaining of documents, 2) identification of entities and their relations, 3) association of entities to linked data resources, and 4) the construction of a schema for the KGs. The experiments were performed over a set of doc- uments in a general and computer science domain. Our method showed encouraging results for the precision in the identification of entities and semantic relationships for the KGs constructed from unstructured texts. Keywords: knowledge graph, construction of graph from texts. 1 Introduction In recent years the Web has become a global repository that represents a source of knowledge in a wide range of domains and languages, where the information is shared and stored in different formats.
    [Show full text]
  • The Resource Description Framework and Its Schema Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma
    The Resource Description Framework and its Schema Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma To cite this version: Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma. The Resource Description Frame- work and its Schema. Handbook of Semantic Web Technologies, 2011, 978-3-540-92912-3. hal- 01171045 HAL Id: hal-01171045 https://hal.inria.fr/hal-01171045 Submitted on 2 Jul 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The Resource Description Framework and its Schema Fabien L. Gandon, INRIA Sophia Antipolis Reto Krummenacher, STI Innsbruck Sung-Kook Han, STI Innsbruck Ioan Toma, STI Innsbruck 1. Abstract RDF is a framework to publish statements on the web about anything. It allows anyone to describe resources, in particular Web resources, such as the author, creation date, subject, and copyright of an image. Any information portal or data-based web site can be interested in using the graph model of RDF to open its silos of data about persons, documents, events, products, services, places etc. RDF reuses the web approach to identify resources (URI) and to allow one to explicitly represent any relationship between two resources.
    [Show full text]