13 research outputs found

    Research on Linked Data and Co-reference Resolution

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    This project report details work carried out in collaboration between the University of Southampton and the Korea Institute of Science and Technology Information, focussing on an RDF dataset of academic authors and publications. Activities included the conversion of the dataset to produce Linked Data, the identification of co-references in and between datasets, and the development of an ontology mapping service to facilitate the integration of the dataset with an existing Semantic Web application, RKBExplorer.com

    Integrating institutional repositories into the Semantic Web

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    The Web has changed the face of scientific communication; and the Semantic Web promises new ways of adding value to research material by making it more accessible to automatic discovery, linking, and analysis. Institutional repositories contain a wealth of information which could benefit from the application of this technology. In this thesis I describe the problems inherent in the informality of traditional repository metadata, and propose a data model based on the Semantic Web which will support more efficient use of this data, with the aim of streamlining scientific communication and promoting efficient use of institutional research output

    Peer-to-peer, multi-agent interaction adapted to a web architecture

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    The Internet and Web have brought in a new era of information sharing and opened up countless opportunities for people to rethink and redefine communication. With the development of network-related technologies, a Client/Server architecture has become dominant in the application layer of the Internet. Nowadays network nodes are behind firewalls and Network Address Translations, and the centralised design of the Client/Server architecture limits communication between users on the client side. Achieving the conflicting goals of data privacy and data openness is difficult and in many cases the difficulty is compounded by the differing solutions adopted by different organisations and companies. Building a more decentralised or distributed environment for people to freely share their knowledge has become a pressing challenge and we need to understand how to adapt the pervasive Client/Server architecture to this more fluid environment. This thesis describes a novel framework by which network nodes or humans can interact and share knowledge with each other through formal service-choreography specifications in a decentralised manner. The platform allows peers to publish, discover and (un)subscribe to those specifications in the form of Interaction Models (IMs). Peer groups can be dynamically formed and disbanded based on the interaction logs of peers. IMs are published in HTML documents as normal Web pages indexable by search engines and associated with lightweight annotations which semantically enhance the embedded IM elements and at the same time make IM publications comply with the Linked Data principles. The execution of IMs is decentralised on each peer via conventional Web browsers, potentially giving the system access to a very large user community. In this thesis, after developing a proof-of-concept implementation, we carry out case studies of the resulting functionality and evaluate the implementation across several metrics. An increasing number of service providers have began to look for customers proactively, and we believe that in the near future we will not search for services but rather services will find us through our peer communities. Our approaches show how a peer-to-peer architecture for this purpose can be obtained on top of a conventional Client/Server Web infrastructure

    Knowledge-centric autonomic systems

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    Autonomic computing revolutionised the commonplace understanding of proactiveness in the digital world by introducing self-managing systems. Built on top of IBM’s structural and functional recommendations for implementing intelligent control, autonomic systems are meant to pursue high level goals, while adequately responding to changes in the environment, with a minimum amount of human intervention. One of the lead challenges related to implementing this type of behaviour in practical situations stems from the way autonomic systems manage their inner representation of the world. Specifically, all the components involved in the control loop have shared access to the system’s knowledge, which, for a seamless cooperation, needs to be kept consistent at all times.A possible solution lies with another popular technology of the 21st century, the Semantic Web,and the knowledge representation media it fosters, ontologies. These formal yet flexible descriptions of the problem domain are equipped with reasoners, inference tools that, among other functions, check knowledge consistency. The immediate application of reasoners in an autonomic context is to ensure that all components share and operate on a logically correct and coherent “view” of the world. At the same time, ontology change management is a difficult task to complete with semantic technologies alone, especially if little to no human supervision is available. This invites the idea of delegating change management to an autonomic manager, as the intelligent control loop it implements is engineered specifically for that purpose.Despite the inherent compatibility between autonomic computing and semantic technologies,their integration is non-trivial and insufficiently investigated in the literature. This gap represents the main motivation for this thesis. Moreover, existing attempts at provisioning autonomic architectures with semantic engines represent bespoke solutions for specific problems (load balancing in autonomic networking, deconflicting high level policies, informing the process of correlating diverse enterprise data are just a few examples). The main drawback of these efforts is that they only provide limited scope for reuse and cross-domain analysis (design guidelines, useful architectural models that would scale well across different applications and modular components that could be integrated in other systems seem to be poorly represented). This work proposes KAS (Knowledge-centric Autonomic System), a hybrid architecture combining semantic tools such as: ‱ an ontology to capture domain knowledge,‱ a reasoner to maintain domain knowledge consistent as well as infer new knowledge, ‱ a semantic querying engine,‱ a tool for semantic annotation analysis with a customised autonomic control loop featuring: ‱ a novel algorithm for extracting knowledge authored by the domain expert, ‱ “software sensors” to monitor user requests and environment changes, ‱ a new algorithm for analysing the monitored changes, matching them against known patterns and producing plans for taking the necessary actions, ‱ “software effectors” to implement the planned changes and modify the ontology accordingly. The purpose of KAS is to act as a blueprint for the implementation of autonomic systems harvesting semantic power to improve self-management. To this end, two KAS instances were built and deployed in two different problem domains, namely self-adaptive document rendering and autonomic decision2support for career management. The former case study is intended as a desktop application, whereas the latter is a large scale, web-based system built to capture and manage knowledge sourced by an entire (relevant) community. The two problems are representative for their own application classes –namely desktop tools required to respond in real time and, respectively, online decision support platforms expected to process large volumes of data undergoing continuous transformation – therefore, they were selected to demonstrate the cross-domain applicability (that state of the art approaches tend to lack) of the proposed architecture. Moreover, analysing KAS behaviour in these two applications enabled the distillation of design guidelines and of lessons learnt from practical implementation experience while building on and adapting state of the art tools and methodologies from both fields.KAS is described and analysed from design through to implementation. The design is evaluated using ATAM (Architecture Trade off Analysis Method) whereas the performance of the two practical realisations is measured both globally as well as deconstructed in an attempt to isolate the impact of each autonomic and semantic component. This last type of evaluation employs state of the art metrics for each of the two domains. The experimental findings show that both instances of the proposed hybrid architecture successfully meet the prescribed high-level goals and that the semantic components have a positive influence on the system’s autonomic behaviour

    Improving data management through automatic information extraction model in ontology for road asset management

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    lRoads are a critical component of transportation infrastructure, and their effective maintenance is paramount in ensuring their continued functionality and safety. This research proposes a novel information management approach based on state-of-the-art deep learning models and ontologies. The approach can automatically extract, integrate, complete, and search for project knowledge buried in unstructured text documents. The approach on the one hand facilitates implementation of modern management approaches, i.e., advanced working packaging to delivery success road management projects, on the other hand improves information management practices in the construction industry

    Linked Data Supported Information Retrieval

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    Um Inhalte im World Wide Web ausfindig zu machen, sind Suchmaschienen nicht mehr wegzudenken. Semantic Web und Linked Data Technologien ermöglichen ein detaillierteres und eindeutiges Strukturieren der Inhalte und erlauben vollkommen neue Herangehensweisen an die Lösung von Information Retrieval Problemen. Diese Arbeit befasst sich mit den Möglichkeiten, wie Information Retrieval Anwendungen von der Einbeziehung von Linked Data profitieren können. Neue Methoden der computer-gestĂŒtzten semantischen Textanalyse, semantischen Suche, Informationspriorisierung und -visualisierung werden vorgestellt und umfassend evaluiert. Dabei werden Linked Data Ressourcen und ihre Beziehungen in die Verfahren integriert, um eine Steigerung der EffektivitĂ€t der Verfahren bzw. ihrer Benutzerfreundlichkeit zu erzielen. ZunĂ€chst wird eine EinfĂŒhrung in die Grundlagen des Information Retrieval und Linked Data gegeben. Anschließend werden neue manuelle und automatisierte Verfahren zum semantischen Annotieren von Dokumenten durch deren VerknĂŒpfung mit Linked Data Ressourcen vorgestellt (Entity Linking). Eine umfassende Evaluation der Verfahren wird durchgefĂŒhrt und das zu Grunde liegende Evaluationssystem umfangreich verbessert. Aufbauend auf den Annotationsverfahren werden zwei neue Retrievalmodelle zur semantischen Suche vorgestellt und evaluiert. Die Verfahren basieren auf dem generalisierten Vektorraummodell und beziehen die semantische Ähnlichkeit anhand von taxonomie-basierten Beziehungen der Linked Data Ressourcen in Dokumenten und Suchanfragen in die Berechnung der Suchergebnisrangfolge ein. Mit dem Ziel die Berechnung von semantischer Ähnlichkeit weiter zu verfeinern, wird ein Verfahren zur Priorisierung von Linked Data Ressourcen vorgestellt und evaluiert. Darauf aufbauend werden Visualisierungstechniken aufgezeigt mit dem Ziel, die Explorierbarkeit und Navigierbarkeit innerhalb eines semantisch annotierten Dokumentenkorpus zu verbessern. HierfĂŒr werden zwei Anwendungen prĂ€sentiert. Zum einen eine Linked Data basierte explorative Erweiterung als ErgĂ€nzung zu einer traditionellen schlĂŒsselwort-basierten Suchmaschine, zum anderen ein Linked Data basiertes Empfehlungssystem

    An Infrastructure for Managing URI Synonymity on the Semantic Web (Poster)

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    The Semantic Web vision involves the production and use of large amounts of RDF data. There have been recent initiatives amongst the Semantic Web community, in particular the Linking Open Data activity and our own ReSIST project, to publish large amounts of RDF that are both interlinked and dereferenceable. The proliferation of such data gives rise to millions of URIs for non-information resources such as people, places and abstract things. Our Consistent Reference Services provide a standard way of managing multiple URIs and finding URI equivalences. The CRS has been designed for use with all linked data Providers and is currently running on a live linked data site

    Organising knowledge in the age of the semantic web: a study of the commensurability of ontologies

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     This study is directed towards the problem of conceptual translation across different data management systems and formats, with a particular focus on those used in the emerging world of the Semantic Web. Increasingly, organisations have sought to connect information sources and services within and beyond their enterprise boundaries, building upon existing Internet facilities to offer improved research, planning, reporting and management capabilities. The Semantic Web is an ambitious response to this growing demand, offering a standards-based platform for sharing, linking and reasoning with information. The imagined result, a globalised knowledge network formed out of mutually referring data structures termed "ontologies", would make possible new kinds of queries, inferences and amalgamations of information. Such a network, though, is premised upon large numbers of manually drawn links between these ontologies. In practice, establishing these links is a complex translation task requiring considerable time and expertise; invariably, as ontologies and other structured information sources are published, many useful connections are neglected. To combat this, in recent years substantial research has been invested into "ontology matching" - the exploration of algorithmic approaches for automatically translating or aligning ontologies. These approaches, which exploit the explicit semantic properties of individual concepts, have registered impressive precision and recall results against humanly-engineered translations. However they are unable to make use of background cultural information about the overall systems in which those concepts are housed - how those systems are used, for what purpose they were designed, what methodological or theoretical principles underlined their construction, and so on. The present study investigates whether paying attention to these sociological dimensions of electronic knowledge systems could supplement algorithmic approaches in some circumstances. Specifically, it asks whether a holistic notion of commensurability can be useful when aligning or translating between such systems.      The first half of the study introduces the problem, surveys the literature, and outlines the general approach. It then proposes both a theoretical foundation and a practical framework for assessing commensurability of ontologies and other knowledge systems. Chapter 1 outlines the Semantic Web, ontologies and the problem of conceptual translation, and poses the key research questions. Conceptual translation can be treated as, by turns, a social, philosophical, linguistic or technological problem; Chapter 2 surveys a correspondingly wide range of literature and approaches.      The methods employed by the study are described in Chapter 3. Chapter 4 critically examines theories of conceptual schemes and commensurability, while Chapter 5 describes the framework itself, comprising a series of specific dimensions, a broad methodological approach, and a means for generating both qualitative and quantitative assessments. The second half of the study then explores the notion of commensurability through several empirical frames. Chapters 6 to 8 applies the framework to a series of case studies. Chapter 6 presents a brief history of knowledge systems, and compares two of these systems - relational databases and Semantic Web ontologies. Chapter 7, in turn, compares several "upper-level" ontologies - reusable schematisations of abstract concepts like Time and Space . Chapter 8 reviews a recent, widely publicised controversy over the standardisation of document formats. This analysis in particular shows how the opaque dry world of technical specifications can reveal the complex network of social dynamics, interests and beliefs which coordinate and motivate them. Collectively, these studies demonstrate the framework is useful in making evident assumptions which motivate the design of different knowledge systems, and further, in assessing the commensurability of those systems. Chapter 9 then presents a further empirical study; here, the framework is implemented as a software system, and pilot tested among a small cohort of researchers. Finally, Chapter 10 summarises the argumentative trajectory of the study as a whole - that, broadly, an elaborated notion of commensurability can tease out important and salient features of translation inscrutable to purely algorithmic methods - and suggests some possibilities for further work
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