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  • × theme_ss:"Semantic Web"
  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"el"
  1. Studer, R.; Studer, H.-P.; Studer, A.: Semantisches Knowledge Retrieval (2001) 0.02 
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    Abstract
    Dieses Whitepaper befasst sich mit der Integration semantischer Technologien in bestehende Ansätze des Information Retrieval und die damit verbundenen weitreichenden Auswirkungen auf Effizienz und Effektivität von Suche und Navigation in Dokumenten. Nach einer Einbettung in die Problematik des Wissensmanagement aus Sicht der Informationstechnik folgt ein Überblick zu den Methoden des Information Retrieval. Anschließend werden die semantischen Technologien "Wissen modellieren - Ontologie" und "Neues Wissen ableiten - Inferenz" vorgestellt. Ein Integrationsansatz wird im Folgenden diskutiert und die entstehenden Mehrwerte präsentiert. Insbesondere ergeben sich Erweiterungen hinsichtlich einer verfeinerten Suchunterstützung und einer kontextbezogenen Navigation sowie die Möglichkeiten der Auswertung von regelbasierten Zusammenhängen und einfache Integration von strukturierten Informationsquellen. Das Whitepaper schließt mit einem Ausblick auf die zukünftige Entwicklung des WWW hin zu einem Semantic Web und die damit verbundenen Implikationen für semantische Technologien.
    Content
    Inhalt: 1. Einführung - 2. Wissensmanagement - 3. Information Retrieval - 3.1. Methoden und Techniken - 3.2. Information Retrieval in der Anwendung - 4. Semantische Ansätze - 4.1. Wissen modellieren - Ontologie - 4.2. Neues Wissen inferieren - 5. Knowledge Retrieval in der Anwendung - 6. Zukunftsaussichten - 7. Fazit
  2. Sigel, A.: Informationsintegration mit semantischen Wissenstechnologien (2006) 0.02 
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    Abstract
    Das Tutorium vermittelt theoretische Grundlagen der wissensorganisatorischen (semantischen) Integration und zeigt auch einige praktische Beispiele. Die Integration bezieht sich auf die Ebenen: Integration von ähnlichen Einträgen in verschiedenen Ontologien (Begriffe und Beziehungen) sowie von Aussagen über gleiche Aussagegegenstände und zugehörige Informationsressourcen. Hierzu werden ausgewählte semantische Wissenstechnologien (Topic Maps und RDF) und -werkzeuge vorgestellt und mit wissensorganisatorischen Grundlagen verbunden (z.B. SKOS - Simple Knowledge Organization Systems, http://www.w3.org/2004/02/skos/, oder Published Resource Identifiers).
    Content
    Tutorium auf der 10. Deutschen ISKO-Tagung (Wissensorganisation 2006): Kompatibilität und Heterogenität in der Wissensorganisation Universität Wien, Montag 03. Juli 2006.
  3. Voß, J.: ¬Das Simple Knowledge Organisation System (SKOS) als Kodierungs- und Austauschformat der DDC für Anwendungen im Semantischen Web (2007) 0.01 
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    Content
    Vortrag beim DDC-Workshop am 01.03.2007 in Göttingen
  4. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.01 
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    Abstract
    One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.
    Date
    12. 2.2011 17:35:22
  5. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.01 
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    Abstract
    More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.
    Date
    26.12.2011 13:40:22
  6. Köstlbacher, A. (Übers.): OWL Web Ontology Language Überblick (2004) 0.01 
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    Abstract
    Die OWL Web Ontology Language wurde entwickelt, um es Anwendungen zu ermöglichen den Inhalt von Informationen zu verarbeiten anstatt die Informationen dem Anwender nur zu präsentieren. OWL erleichtert durch zusätzliches Vokabular in Verbindung mit formaler Semantik stärkere Interpretationsmöglichkeiten von Web Inhalten als dies XML, RDF und RDFS ermöglichen. OWL besteht aus drei Untersprachen mit steigender Ausdrucksmächtigkeit: OWL Lite, OWL DL and OWL Full. Dieses Dokument wurde für Leser erstellt, die einen ersten Eindruck von den Möglichkeiten bekommen möchten, die OWL bietet. Es stellt eine Einführung in OWL anhand der Beschreibung der Merkmale der drei Untersprachen von OWL dar. Kenntnisse von RDF Schema sind hilfreich für das Verständnis, aber nicht unbedingt erforderlich. Nach der Lektüre dieses Dokuments können sich interessierte Leser für detailliertere Beschreibungen und ausführliche Beispiele der Merkmale von OWL dem OWL Guide zuwenden. Die normative formale Definition von OWL findet sich unter OWL Semantics and Abstract Syntax.
  7. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.01 
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    Abstract
    Semantic Web knowledge representation standards, and in particular RDF and OWL, often come endowed with a formal semantics which is considered to be of fundamental importance for the field. Reasoning, i.e., the drawing of logical inferences from knowledge expressed in such standards, is traditionally based on logical deductive methods and algorithms which can be proven to be sound and complete and terminating, i.e. correct in a very strong sense. For various reasons, though, in particular the scalability issues arising from the ever increasing amounts of Semantic Web data available and the inability of deductive algorithms to deal with noise in the data, it has been argued that alternative means of reasoning should be investigated which bear high promise for high scalability and better robustness. From this perspective, deductive algorithms can be considered the gold standard regarding correctness against which alternative methods need to be tested. In this paper, we show that it is possible to train a Deep Learning system on RDF knowledge graphs, such that it is able to perform reasoning over new RDF knowledge graphs, with high precision and recall compared to the deductive gold standard.
    Date
    16.11.2018 14:22:01
  8. Ulrich, W.: Simple Knowledge Organisation System (2007) 0.01 
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    Content
    Semantic Web - Taxonomie und Thesaurus - SKOS - Historie - Klassen und Eigenschaften - Beispiele - Generierung - automatisiert - per Folksonomie - Fazit und Ausblick
  9. Hüsken, P.: Information Retrieval im Semantic Web (2006) 0.01 
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    Abstract
    Das Semantic Web bezeichnet ein erweitertes World Wide Web (WWW), das die Bedeutung von präsentierten Inhalten in neuen standardisierten Sprachen wie RDF Schema und OWL modelliert. Diese Arbeit befasst sich mit dem Aspekt des Information Retrieval, d.h. es wird untersucht, in wie weit Methoden der Informationssuche sich auf modelliertes Wissen übertragen lassen. Die kennzeichnenden Merkmale von IR-Systemen wie vage Anfragen sowie die Unterstützung unsicheren Wissens werden im Kontext des Semantic Web behandelt. Im Fokus steht die Suche nach Fakten innerhalb einer Wissensdomäne, die entweder explizit modelliert sind oder implizit durch die Anwendung von Inferenz abgeleitet werden können. Aufbauend auf der an der Universität Duisburg-Essen entwickelten Retrievalmaschine PIRE wird die Anwendung unsicherer Inferenz mit probabilistischer Prädikatenlogik (pDatalog) implementiert.
  10. OWL Web Ontology Language Test Cases (2004) 0.00 
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    Date
    14. 8.2011 13:33:22
  11. Scheir, P.; Pammer, V.; Lindstaedt, S.N.: Information retrieval on the Semantic Web : does it exist? (2007) 0.00 
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    Content
    Enthält einen Überblick über Modelle, Systeme und Projekte
  12. RDF/XML Syntax Specification (Revised) : W3C Recommendation 10 February 2004 (2004) 0.00 
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    Abstract
    The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This document defines an XML syntax for RDF called RDF/XML in terms of Namespaces in XML, the XML Information Set and XML Base. The formal grammar for the syntax is annotated with actions generating triples of the RDF graph as defined in RDF Concepts and Abstract Syntax. The triples are written using the N-Triples RDF graph serializing format which enables more precise recording of the mapping in a machine processable form. The mappings are recorded as tests cases, gathered and published in RDF Test Cases.
  13. Mirizzi, R.: Exploratory browsing in the Web of Data (2011) 0.00 
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    Abstract
    Thanks to the recent Linked Data initiative, the foundations of the Semantic Web have been built. Shared, open and linked RDF datasets give us the possibility to exploit both the strong theoretical results and the robust technologies and tools developed since the seminal paper in the Semantic Web appeared in 2001. In a simplistic way, we may think at the Semantic Web as a ultra large distributed database we can query to get information coming from different sources. In fact, every dataset exposes a SPARQL endpoint to make the data accessible through exact queries. If we know the URI of the famous actress Nicole Kidman in DBpedia we may retrieve all the movies she acted with a simple SPARQL query. Eventually we may aggregate this information with users ratings and genres from IMDB. Even though these are very exciting results and applications, there is much more behind the curtains. Datasets come with the description of their schema structured in an ontological way. Resources refer to classes which are in turn organized in well structured and rich ontologies. Exploiting also this further feature we go beyond the notion of a distributed database and we can refer to the Semantic Web as a distributed knowledge base. If in our knowledge base we have that Paris is located in France (ontological level) and that Moulin Rouge! is set in Paris (data level) we may query the Semantic Web (interpreted as a set of interconnected datasets and related ontologies) to return all the movies starred by Nicole Kidman set in France and Moulin Rouge! will be in the final result set. The ontological level makes possible to infer new relations among data.
    The Linked Data initiative and the state of the art in semantic technologies led off all brand new search and mash-up applications. The basic idea is to have smarter lookup services for a huge, distributed and social knowledge base. All these applications catch and (re)propose, under a semantic data perspective, the view of the classical Web as a distributed collection of documents to retrieve. The interlinked nature of the Web, and consequently of the Semantic Web, is exploited (just) to collect and aggregate data coming from different sources. Of course, this is a big step forward in search and Web technologies, but if we limit our investi- gation to retrieval tasks, we miss another important feature of the current Web: browsing and in particular exploratory browsing (a.k.a. exploratory search). Thanks to its hyperlinked nature, the Web defined a new way of browsing documents and knowledge: selection by lookup, navigation and trial-and-error tactics were, and still are, exploited by users to search for relevant information satisfying some initial requirements. The basic assumptions behind a lookup search, typical of Information Retrieval (IR) systems, are no more valid in an exploratory browsing context. An IR system, such as a search engine, assumes that: the user has a clear picture of what she is looking for ; she knows the terminology of the specific knowledge space. On the other side, as argued in, the main challenges in exploratory search can be summarized as: support querying and rapid query refinement; other facets and metadata-based result filtering; leverage search context; support learning and understanding; other visualization to support insight/decision making; facilitate collaboration. In Section 3 we will show two applications for exploratory search in the Semantic Web addressing some of the above challenges.
  14. Gómez-Pérez, A.; Corcho, O.: Ontology languages for the Semantic Web (2015) 0.00 
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    Abstract
    Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.
  15. Menzel, C.: Knowledge representation, the World Wide Web, and the evolution of logic (2011) 0.00 
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    Abstract
    In this paper, I have traced a series of evolutionary adaptations of FOL motivated entirely by its use by knowledge engineers to represent and share information on the Web culminating in the development of Common Logic. While the primary goal in this paper has been to document this evolution, it is arguable, I think that CL's syntactic and semantic egalitarianism better realizes the goal "topic neutrality" that a logic should ideally exemplify - understood, at least in part, as the idea that logic should as far as possible not itself embody any metaphysical presuppositions. Instead of retaining the traditional metaphysical divisions of FOL that reflect its Fregean origins, CL begins as it were with a single, metaphysically homogeneous domain in which, potentially, anything can play the traditional roles of object, property, relation, and function. Note that the effect of this is not to destroy traditional metaphysical divisions. Rather, it simply to refrain from building those divisions explicitly into one's logic; instead, such divisions are left to the user to introduce and enforce axiomatically in an explicit metaphysical theory.
  16. Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012) 0.00 
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    Abstract
    In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.
    Content
    Thesis submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University in partial fulfilment of the requirements for the degree of Master of science in Computer Engineering (XII, 57 S.)
  17. RDF Vocabulary Description Language 1.0 : RDF Schema (2004) 0.00 
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    Abstract
    The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This specification describes how to use RDF to describe RDF vocabularies. This specification defines a vocabulary for this purpose and defines other built-in RDF vocabulary initially specified in the RDF Model and Syntax Specification.
  18. SKOS Simple Knowledge Organization System Primer (2009) 0.00 
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    Abstract
    SKOS (Simple Knowledge Organisation System) provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other types of controlled vocabulary. As an application of the Resource Description Framework (RDF) SKOS allows concepts to be documented, linked and merged with other data, while still being composed, integrated and published on the World Wide Web. This document is an implementors guide for those who would like to represent their concept scheme using SKOS. In basic SKOS, conceptual resources (concepts) can be identified using URIs, labelled with strings in one or more natural languages, documented with various types of notes, semantically related to each other in informal hierarchies and association networks, and aggregated into distinct concept schemes. In advanced SKOS, conceptual resources can be mapped to conceptual resources in other schemes and grouped into labelled or ordered collections. Concept labels can also be related to each other. Finally, the SKOS vocabulary itself can be extended to suit the needs of particular communities of practice.
  19. Zhang, L.; Liu, Q.L.; Zhang, J.; Wang, H.F.; Pan, Y.; Yu, Y.: Semplore: an IR approach to scalable hybrid query of Semantic Web data (2007) 0.00 
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    Abstract
    As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find information more precisely on the Semantic Web, keyword searches are still needed to help exploit textual information. It thus becomes very important that we can combine precise structured queries with imprecise keyword searches to have a hybrid query capability. In addition, due to the huge volume of information on the Semantic Web, the hybrid query must be processed in a very scalable way. In this paper, we define such a hybrid query capability that combines unary tree-shaped structured queries with keyword searches. We show how existing information retrieval (IR) index structures and functions can be reused to index semantic web data and its textual information, and how the hybrid query is evaluated on the index structure using IR engines in an efficient and scalable manner. We implemented this IR approach in an engine called Semplore. Comprehensive experiments on its performance show that it is a promising approach. It leads us to believe that it may be possible to evolve current web search engines to query and search the Semantic Web. Finally, we briefy describe how Semplore is used for searching Wikipedia and an IBM customer's product information.
    Series
    Lecture notes in computer science; 4825
  20. Veltman, K.H.: Towards a Semantic Web for culture 0.00 
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    Abstract
    Today's semantic web deals with meaning in a very restricted sense and offers static solutions. This is adequate for many scientific, technical purposes and for business transactions requiring machine-to-machine communication, but does not answer the needs of culture. Science, technology and business are concerned primarily with the latest findings, the state of the art, i.e. the paradigm or dominant world-view of the day. In this context, history is considered non-essential because it deals with things that are out of date. By contrast, culture faces a much larger challenge, namely, to re-present changes in ways of knowing; changing meanings in different places at a given time (synchronically) and over time (diachronically). Culture is about both objects and the commentaries on them; about a cumulative body of knowledge; about collective memory and heritage. Here, history plays a central role and older does not mean less important or less relevant. Hence, a Leonardo painting that is 400 years old, or a Greek statue that is 2500 years old, typically have richer commentaries and are often more valuable than their contemporary equivalents. In this context, the science of meaning (semantics) is necessarily much more complex than semantic primitives. A semantic web in the cultural domain must enable us to trace how meaning and knowledge organisation have evolved historically in different cultures. This paper examines five issues to address this challenge: 1) different world-views (i.e. a shift from substance to function and from ontology to multiple ontologies); 2) developments in definitions and meaning; 3) distinctions between words and concepts; 4) new classes of relations; and 5) dynamic models of knowledge organisation. These issues reveal that historical dimensions of cultural diversity in knowledge organisation are also central to classification of biological diversity. New ways are proposed of visualizing knowledge using a time/space horizon to distinguish between universals and particulars. It is suggested that new visualization methods make possible a history of questions as well as of answers, thus enabling dynamic access to cultural and historical dimensions of knowledge. Unlike earlier media, which were limited to recording factual dimensions of collective memory, digital media enable us to explore theories, ways of perceiving, ways of knowing; to enter into other mindsets and world-views and thus to attain novel insights and new levels of tolerance. Some practical consequences are outlined.

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