1,058 research outputs found

    Lynx: A knowledge-based AI service platform for content processing, enrichment and analysis for the legal domain

    Get PDF
    The EU-funded project Lynx focuses on the creation of a knowledge graph for the legal domain (Legal Knowledge Graph, LKG) and its use for the semantic processing, analysis and enrichment of documents from the legal domain. This article describes the use cases covered in the project, the entire developed platform and the semantic analysis services that operate on the documents. © 202

    Knowledge Base Enrichment by Relation Learning from Social Tagging Data

    Get PDF
    There has been considerable interest in transforming unstructured social tagging data into structured knowledge for semantic-based retrieval and recommendation. Research in this line mostly exploits data co-occurrence and often overlooks the complex and ambiguous meanings of tags. Furthermore, there have been few comprehensive evaluation studies regarding the quality of the discovered knowledge. We propose a supervised learning method to discover subsumption relations from tags. The key to this method is quantifying the probabilistic association among tags to better characterise their relations. We further develop an algorithm to organise tags into hierarchies based on the learned relations. Experiments were conducted using a large, publicly available dataset, Bibsonomy, and three popular, human-engineered or data-driven knowledge bases: DBpedia, Microsoft Concept Graph, and ACM Computing Classification System. We performed a comprehensive evaluation using different strategies: relation-level, ontology-level, and knowledge base enrichment based evaluation. The results clearly show that the proposed method can extract knowledge of better quality than the existing methods against the gold standard knowledge bases. The proposed approach can also enrich knowledge bases with new subsumption relations, having the potential to significantly reduce time and human effort for knowledge base maintenance and ontology evolution

    Pattern-based design applied to cultural heritage knowledge graphs

    Full text link
    Ontology Design Patterns (ODPs) have become an established and recognised practice for guaranteeing good quality ontology engineering. There are several ODP repositories where ODPs are shared as well as ontology design methodologies recommending their reuse. Performing rigorous testing is recommended as well for supporting ontology maintenance and validating the resulting resource against its motivating requirements. Nevertheless, it is less than straightforward to find guidelines on how to apply such methodologies for developing domain-specific knowledge graphs. ArCo is the knowledge graph of Italian Cultural Heritage and has been developed by using eXtreme Design (XD), an ODP- and test-driven methodology. During its development, XD has been adapted to the need of the CH domain e.g. gathering requirements from an open, diverse community of consumers, a new ODP has been defined and many have been specialised to address specific CH requirements. This paper presents ArCo and describes how to apply XD to the development and validation of a CH knowledge graph, also detailing the (intellectual) process implemented for matching the encountered modelling problems to ODPs. Relevant contributions also include a novel web tool for supporting unit-testing of knowledge graphs, a rigorous evaluation of ArCo, and a discussion of methodological lessons learned during ArCo development

    Enabling European Archaeological Research: The ARIADNE E-Infrastructure

    Get PDF
    In the last 20 years, e-infrastructures have become ever more important for the conduct and progress of research in all branches of scientific enterprise. Increasingly collaborative, distributed and data-intensive research requires the sharing of resources (data, tools, computing facilities) via e-infrastructure as well as support for effective co-operation among research groups (ESF 2011; ESFRI 2016). Moreover there is the expectation that with large datasets ('big data'), e-infrastructure and advanced computing techniques, new scientific questions can be tackled. The archaeological research community has been an early adopter of various digital methods and tools for data acquisition, organisation, analysis and presentation of research results of individual projects. The provision of e-infrastructure and services for data sharing, discovery, access and re-use for the heritage sector is, however, lagging behind other research fields, such as the natural and life sciences. The consequence is a high level of fragmentation of archaeological data and limited capability for collaborative research across institutional and national as well as disciplinary boundaries (Aspöck and Geser 2014). This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This e-infrastructure initiative is being promoted by a consortium of archaeological institutes, data archives and technology developers, and funded under the European Commission's Seventh Framework Programme (ARIADNE 2014a; Niccolucci and Richards 2013). ARIADNE enables archaeological data providers, large and small, to register and connect their resources (datasets, collections) to the e-infrastructure, and a data portal provides search, access and other services across the integrated resources. The portal puts into operation a proof of concept exemplar first developed under the ARENA (Archaeological Records of Europe Networked Access) project (Kenny and Richards 2005; Kilbride 2004), itself inspired by a proposal made by Hansen (1993). ARIADNE integrates resource discovery metadata using various controlled vocabularies, e.g. the W3C Data Catalogue Vocabulary (adapted for describing archaeological datasets), subject thesauri, gazetteers, chronologies, and the CIDOC Conceptual Reference Model (CRM). Based on this integration the data portal offers several ways to search and access resources made available by data providers located in different countries. ARIADNE thus acts as a broker between data providers and users and offers additional web services for products such as high-resolution images, Reflectance Transformation Imaging (RTI), 3D objects and landscapes. Employing such services in research projects or for content deposited in digital archives will greatly enhance the ability of researchers to publish, access and study archaeological content online. ARIADNE therefore represents a substantial advance for archaeology; in particular it provides a common platform where dispersed data resources can be uniformly described, discovered and accessed. It is also an essential step towards the even more ambitious goal of offering archaeologists integrated data, tools and computing resources for web-based research that creates new knowledge (e-archaeology). The next section describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realise. The results of the ARIADNE user surveys undertaken to match expectations and requirements for the e-infrastructure and data portal services are then presented. The main part of the article describes ARIADNE's overall architecture, core services (data registration, discovery and access) and other extant or experimental services. A further section presents the on-going evaluation of the data integration and set of services. Finally, the article summarises some lessons already learned in the integration of data resources and services, and considers the prospects for the wider engagement of the archaeological research community in sharing data through the ARIADNE e-infrastructure and portal

    Enabling European archaeological research: The ARIADNE E-infrastructure

    Get PDF
    Research e-infrastructures, digital archives and data services have become important pillars of scientific enterprise that in recent decades has become ever more collaborative, distributed and data-intensive. The archaeological research community has been an early adopter of digital tools for data acquisition, organisation, analysis and presentation of research results of individual projects. However, the provision of einfrastructure and services for data sharing, discovery, access and re-use has lagged behind. This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This EUfunded network has developed an einfrastructure that enables data providers to register and provide access to their resources (datasets, collections) through the ARIADNE data portal, facilitating discovery, access and other services across the integrated resources. This article describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realise. The results of the ARIADNE surveys on users' expectations and requirements are also presented. The main section of the article describes the architecture of the einfrastructure, core services (data registration, discovery and access) and various other extant or experimental services. The ongoing evaluation of the data integration and services is also discussed. Finally, the article summarises lessons learned, and outlines the prospects for the wider engagement of the archaeological research community in sharing data through ARIADNE

    Ontology mapping with auxiliary resources

    Get PDF

    Semantic Systems. The Power of AI and Knowledge Graphs

    Get PDF
    This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies

    many faces, many places (Term21)

    Get PDF
    UIDB/03213/2020 UIDP/03213/2020Proceedings of the LREC 2022 Workshop Language Resources and Evaluation Conferencepublishersversionpublishe

    many faces, many places (Term21)

    Get PDF
    UIDB/03213/2020 UIDP/03213/2020publishersversionpublishe

    A planetary nervous system for social mining and collective awareness

    Get PDF
    We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good. Graphical abstrac
    corecore