Search (65 results, page 1 of 4)

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Abstract

By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.

Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

Theme

Semantic Web

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Abstract

Plenty of contemporary attempts to search exist that are associated with the area of Semantic Web. But which of them qualify as information retrieval for the Semantic Web? Do such approaches exist? To answer these questions we take a look at the nature of the Semantic Web and Semantic Desktop and at definitions for information and data retrieval. We survey current approaches referred to by their authors as information retrieval for the Semantic Web or that use Semantic Web technology for search.

Theme

Semantic Web

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Content

Part I. Analyzing the state of the art - What is semantic search? Part II. The proposal - An ontology-based IR model - Semantic retrieval on the Web Part III. Extensions - Semantic knowledge gateway - Coping with knowledge incompleteness

Theme

Semantic Web

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Abstract

This book constitutes the refereed proceedings of the Second European Semantic Web Conference, ESWC 2005, heldin Heraklion, Crete, Greece in May/June 2005. The 48 revised full papers presented were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on semantic Web services, languages, ontologies, reasoning and querying, search and information retrieval, user and communities, natural language for the semantic Web, annotation tools, and semantic Web applications.

LCSH

Information storage and retrieval systems

RSWK

Semantic Web / Kongress / Iraklion <2005>
Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Iraklion <2005>

Subject

Semantic Web / Kongress / Iraklion <2005>
Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Iraklion <2005>
Information storage and retrieval systems

Theme

Semantic Web

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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.

Footnote

Zugl.: Dortmund, Univ., Dipl.-Arb., 2006 u.d.T.: Hüsken, Peter: Information-Retrieval im Semantic-Web.

RSWK

Information Retrieval / Semantic Web

Subject

Information Retrieval / Semantic Web

Theme

Semantic Web

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Abstract

This article introduces the Simple Knowledge Organisation System (SKOS), a Semantic Web language for representing controlled structured vocabularies, including thesauri, classification schemes, subject heading systems and taxonomies. SKOS provides a framework for publishing thesauri, classification schemes, and subject indexes on the Web, and for applying these systems to resource collections that are part of the SemanticWeb. SemanticWeb applications may harvest and merge SKOS data, to integrate and enhances retrieval service across multiple collections (e.g. libraries). This article also describes some alternatives for integrating Semantic Web services based on the Resource Description Framework (RDF) and SKOS into a distributed enterprise architecture.

Footnote

Simultaneously published as Knitting the Semantic Web

Theme

Semantic Web

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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.

Source

Proceeding ISWC'07/ASWC'07 : Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference. Ed.: K. Aberer et al

Theme

Semantic Web

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Abstract

Das wachsende Informationsvolumen im WWW führt paradoxerweise zu einer immer schwierigeren Nutzung, das Finden und Verknüpfen von Informationen in einem unstrukturierten Umfeld wird zur Sisyphosarbeit. Hier versprechen Semantic-Web-Ansätze Abhilfe. Die Autoren beschreiben Technologien, wie eine semantische Integration verteilter Daten durch verteilte Ontologien erreicht werden kann. Diese Techniken sind sowohl für Forscher als auch für Professionals interessant, die z.B. die Integration von Produktdaten aus verteilten Datenbanken im WWW oder von lose miteinander verbunden Anwendungen in verteilten Organisationen implementieren sollen.

LCSH

Semantic Web
Ontologies (Information retrieval)

RSWK

Semantic Web / Ontologie <Wissensverarbeitung> / Information Retrieval / Verteilung / Metadaten / Datenintegration

Subject

Semantic Web / Ontologie <Wissensverarbeitung> / Information Retrieval / Verteilung / Metadaten / Datenintegration
Semantic Web
Ontologies (Information retrieval)

Theme

Semantic Web

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Abstract

The Semantic Web realization depends on the availability of a critical mass of metadata for the web content, associated with the respective formal knowledge about the world. We claim that the Semantic Web, at its current stage of development, is in a state of a critical need of metadata generation and usage schemata that are specific, well-defined and easy to understand. This paper introduces our vision for a holistic architecture for semantic annotation, indexing, and retrieval of documents with regard to extensive semantic repositories. A system (called KIM), implementing this concept, is presented in brief and it is used for the purposes of evaluation and demonstration. A particular schema for semantic annotation with respect to real-world entities is proposed. The underlying philosophy is that a practical semantic annotation is impossible without some particular knowledge modelling commitments. Our understanding is that a system for such semantic annotation should be based upon a simple model of real-world entity classes, complemented with extensive instance knowledge. To ensure the efficiency, ease of sharing, and reusability of the metadata, we introduce an upper-level ontology (of about 250 classes and 100 properties), which starts with some basic philosophical distinctions and then goes down to the most common entity types (people, companies, cities, etc.). Thus it encodes many of the domain-independent commonsense concepts and allows straightforward domain-specific extensions. On the basis of the ontology, a large-scale knowledge base of entity descriptions is bootstrapped, and further extended and maintained. Currently, the knowledge bases usually scales between 105 and 106 descriptions. Finally, this paper presents a semantically enhanced information extraction system, which provides automatic semantic annotation with references to classes in the ontology and to instances. The system has been running over a continuously growing document collection (currently about 0.5 million news articles), so it has been under constant testing and evaluation for some time now. On the basis of these semantic annotations, we perform semantic based indexing and retrieval where users can mix traditional information retrieval (IR) queries and ontology-based ones. We argue that such large-scale, fully automatic methods are essential for the transformation of the current largely textual web into a Semantic Web.

Source

Web semantics: science, services and agents on the World Wide Web. 2(2004) no.1, S.49-79

Theme

Semantic Web

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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.

Theme

Semantic Web

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Abstract

This chapter presents ontologies and their role in the creation of the Semantic Web. Ontologies hold special interest, because they are very closely related to the way we understand the world. They provide common understanding, the very first step to successful communication. In following sections, we will present ontologies, how they are created and used. We will describe available tools for specifying and working with ontologies.

Date

31. 7.2010 16:58:22

Source

Semantic digital libraries. Eds.: S.R. Kruk, B. McDaniel

Theme

Semantic Web

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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

Series

Ontoprise "Semantics for the Web" - Whitepaper series

Theme

Semantic Web

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Abstract

Significant progress has been made in technologies for publishing and distributing knowledge and information on the web. However, much of the published information is not organized, and it is hard to find answers to questions that require more than a keyword search. In general, one can say that the web is organizing itself. Information is often published in relatively ad hoc fashion. Typically, concern about the presentation of content has been limited to purely layout issues. This, combined with the fact that the representation language used on the World Wide Web (HTML) is mainly format-oriented, makes publishing on the WWW easy, giving it an enormous expressiveness. People add private, educational or organizational content to the web that is of an immensely diverse nature. Content on the web is growing closer to a real universal knowledge base, with one problem relatively undefined; the problem of the interpretation of its contents. Although widely acknowledged for its general and universal advantages, the increasing popularity of the web also shows us some major drawbacks. The developments of the information content on the web during the last year alone, clearly indicates the need for some changes. Perhaps one of the most significant problems with the web as a distributed information system is the difficulty of finding and comparing information.
Thus, there is a clear need for the web to become more semantic. The aim of introducing semantics into the web is to enhance the precision of search, but also enable the use of logical reasoning on web contents in order to answer queries. The CORPORUM OntoBuilder toolset is developed specifically for this task. It consists of a set of applications that can fulfil a variety of tasks, either as stand-alone tools, or augmenting each other. Important tasks that are dealt with by CORPORUM are related to document and information retrieval (find relevant documents, or support the user finding them), as well as information extraction (building a knowledge base from web documents to answer queries), information dissemination (summarizing strategies and information visualization), and automated document classification strategies. First versions of the toolset are encouraging in that they show large potential as a supportive technology for building up the Semantic Web. In this chapter, methods for transforming the current web into a semantic web are discussed, as well as a technical solution that can perform this task: the CORPORUM tool set. First, the toolset is introduced; followed by some pragmatic issues relating to the approach; then there will be a short overview of the theory in relation to CognIT's vision; and finally, a discussion on some of the applications that arose from the project.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Abstract

This document contains and presents test cases for the Web Ontology Language (OWL) approved by the Web Ontology Working Group. Many of the test cases illustrate the correct usage of the Web Ontology Language (OWL), and the formal meaning of its constructs. Other test cases illustrate the resolution of issues considered by the Working Group. Conformance for OWL documents and OWL document checkers is specified.

Date

14. 8.2011 13:33:22

Theme

Semantic Web

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Abstract

Integrated digital access to multiple collections is a prominent issue for many Cultural Heritage institutions. The metadata describing diverse collections must be interoperable, which requires aligning the controlled vocabularies that are used to annotate objects from these collections. In this paper, we present an experiment where we match the vocabularies of two collections by applying the Knowledge Representation techniques established in recent Semantic Web research. We discuss the steps that are required for such matching, namely formalising the initial resources using Semantic Web languages, and running ontology mapping tools on the resulting representations. In addition, we present a prototype that enables the user to browse the two collections using the obtained alignment while still providing her with the original vocabulary structures.

Source

Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006

Theme

Semantic Web

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Abstract

Important information is often scattered across Web and/or intranet resources. Traditional search engines return ranked retrieval lists that offer little or no information on the semantic relationships among documents. Knowledge workers spend a substantial amount of their time browsing and reading to find out how documents are related to one another and where each falls into the overall structure of the problem domain. Yet only when knowledge workers begin to locate the similarities and differences among pieces of information do they move into an essential part of their work: building relationships to create new knowledge. Information retrieval traditionally focuses on the relationship between a given query (or user profile) and the information store. On the other hand, exploitation of interrelationships between selected pieces of information (which can be facilitated by the use of ontologies) can put otherwise isolated information into a meaningful context. The implicit structures so revealed help users use and manage information more efficiently. Knowledge management tools are needed that integrate the resources dispersed across Web resources into a coherent corpus of interrelated information. Previous research in information integration has largely focused on integrating heterogeneous databases and knowledge bases, which represent information in a highly structured way, often by means of formal languages. In contrast, the Web consists to a large extent of unstructured or semi-structured natural language texts. As we have seen, ontologies offer an alternative way to cope with heterogeneous representations of Web resources. The domain model implicit in an ontology can be taken as a unifying structure for giving information a common representation and semantics. Once such a unifying structure exists, it can be exploited to improve browsing and retrieval performance in information access tools. QuizRDF is an example of such a tool.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Content

Semantic Web - Taxonomie und Thesaurus - SKOS - Historie - Klassen und Eigenschaften - Beispiele - Generierung - automatisiert - per Folksonomie - Fazit und Ausblick

Theme

Semantic Web

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Abstract

The global economy is rapidly becoming more and more knowledge intensive. Knowledge is now widely recognized as the fourth production factor, on an equal footing with the traditional production factors of labour, capital and materials. Managing knowledge is as important as the traditional management of labour, capital and materials. In this book, we have shown how Semantic Web technology can make an important contribution to knowledge management.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Abstract

Social Tagging als freie Verschlagwortung durch Nutzer im Web wird immer häufiger mit der Idee des Semantic Web in Zusammenhang gebracht. Wie beide Konzepte in der Praxis konkret zusammenkommen sollen, bleibt jedoch meist unklar. Dieser Artikel soll hier Aufklärung leisten, indem die Kombination von Social Tagging und Semantic Web in Form von Semantic Tagging mit dem Simple Knowledge Organisation System dargestellt und auf die konkreten Möglichkeiten, Vorteile und offenen Fragen der Semantischen Indexierung eingegangen wird.

Theme

Semantic Web

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Abstract

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Source

Web semantics: science, services and agents on the World Wide Web. 4(2006) no.1, S.14-28

Theme

Semantic Web