Search (116 results, page 1 of 6)

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Abstract

In der vorliegenden Arbeit soll einen Ansatz zur Implementation einer Wissensrepräsentation mit den in Abschnitt 1.1. skizzierten Eigenschaften und dem Semantic Web als Anwendungsbereich vorgestellt werden. Die Arbeit ist im Wesentlichen in zwei Bereiche gegliedert: dem Untersuchungsbereich (Kapitel 2-5), in dem ich die in Abschnitt 1.1. eingeführte Terminologie definiert und ein umfassender Überblick über die zugrundeliegenden Konzepte gegeben werden soll, und dem Implementationsbereich (Kapitel 6), in dem aufbauend auf dem im Untersuchungsbereich erarbeiteten Wissen einen semantischen Suchdienst entwickeln werden soll. In Kapitel 2 soll zunächst das Konzept der semantischen Interpretation erläutert und in diesem Kontext hauptsächlich zwischen Daten, Information und Wissen unterschieden werden. In Kapitel 3 soll Wissensrepräsentation aus einer kognitiven Perspektive betrachtet und in diesem Zusammenhang das Konzept der Unschärfe beschrieben werden. In Kapitel 4 sollen sowohl aus historischer als auch aktueller Sicht die Ansätze zur Wissensrepräsentation und -auffindung beschrieben und in diesem Zusammenhang das Konzept der Unschärfe diskutiert werden. In Kapitel 5 sollen die aktuell im WWW eingesetzten Modelle und deren Einschränkungen erläutert werden. Anschließend sollen im Kontext der Entscheidungsfindung die Anforderungen beschrieben werden, die das WWW an eine adäquate Wissensrepräsentation stellt, und anhand der Technologien des Semantic Web die Repräsentationsparadigmen erläutert werden, die diese Anforderungen erfüllen. Schließlich soll das Topic Map-Paradigma erläutert werden. In Kapitel 6 soll aufbauend auf die im Untersuchtungsbereich gewonnenen Erkenntnisse ein Prototyp entwickelt werden. Dieser besteht im Wesentlichen aus Softwarewerkzeugen, die das automatisierte und computergestützte Extrahieren von Informationen, das unscharfe Modellieren, sowie das Auffinden von Wissen unterstützen. Die Implementation der Werkzeuge erfolgt in der Programmiersprache Java, und zur unscharfen Wissensrepräsentation werden Topic Maps eingesetzt. Die Implementation wird dabei schrittweise vorgestellt. Schließlich soll der Prototyp evaluiert und ein Ausblick auf zukünftige Erweiterungsmöglichkeiten gegeben werden. Und schließlich soll in Kapitel 7 eine Synthese formuliert werden.

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Content

"Swoogle, the Semantic web search engine, is a research project carried out by the ebiquity research group in the Computer Science and Electrical Engineering Department at the University of Maryland. It's an engine tailored towards finding documents on the semantic web. The whole research paper is available here. Semantic web is touted as the next generation of online content representation where the web documents are represented in a language that is not only easy for humans but is machine readable (easing the integration of data as never thought possible) as well. And the main elements of the semantic web include data model description formats such as Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, Turtle, N-Triples), and notations such as RDF Schema (RDFS), the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain (Wikipedia). And Swoogle is an attempt to mine and index this new set of web documents. The engine performs crawling of semantic documents like most web search engines and the search is available as web service too. The engine is primarily written in Java with the PHP used for the front-end and MySQL for database. Swoogle is capable of searching over 10,000 ontologies and indexes more that 1.3 million web documents. It also computes the importance of a Semantic Web document. The techniques used for indexing are the more google-type page ranking and also mining the documents for inter-relationships that are the basis for the semantic web. For more information on how the RDF framework can be used to relate documents, read the link here. Being a research project, and with a non-commercial motive, there is not much hype around Swoogle. However, the approach to indexing of Semantic web documents is an approach that most engines will have to take at some point of time. When the Internet debuted, there were no specific engines available for indexing or searching. The Search domain only picked up as more and more content became available. One fundamental question that I've always wondered about it is - provided that the search engines return very relevant results for a query - how to ascertain that the documents are indeed the most relevant ones available. There is always an inherent delay in indexing of document. Its here that the new semantic documents search engines can close delay. Experimenting with the concept of Search in the semantic web can only bore well for the future of search technology."

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Abstract

The unstructured design of Web resources favors human comprehension, but makes difficult the automatic exploitation of the contents of these resources by machines. So, the Semantic Web aims at making the cooperation between human and machine possible, by giving any information a well defined meaning. The first weavings of the Semantic Web are already prepared. Machines become able to treat and understand the data that were accustomed to only visualization, by using ontologies constitute an essential element of the Semantic Web, as they serve as a form of knowledge representation, sharing, and reuse. However, the Web content is subject to imperfection, and crisp ontologies become less suitable to represent concepts with imprecise definitions. To overcome this problem, fuzzy ontologies constitute a promising research orientation. Indeed, the definition of fuzzy ontologies components constitutes an issue that needs to be well treated. It is necessary to have an appropriate methodology of building an operationalization of fuzzy ontological models. This chapter defines a fuzzy ontological model based on fuzzy description logic. This model uses a new approach for the formal description of fuzzy ontologies. This new methodology shows how all the basic components defined for fuzzy ontologies can be constructed.

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Abstract

Primitive thinking forms affected the organization of knowledge, and at a later date writing also affected organization. Currently, the web requires new forms of learning and knowledge; with the globalization of information, connectivity and virtuality have a bearing on human thought. Digital thinking is shaping our reality and its organizational form. Natural memory, considered to be a process that requires the structure of natural language and human capabilities, is interwoven with a subject and a conscience; memory preserved through writing required other tools to assist it, and classifications, cataloguing, organization or other KOS were created. The new tool for recovering digital memory is the semantic web. This points to information's future on the Internet and seems to approach the utopia of global, organized information and attempts to give the website greater significance. The Web 3.0 incorporates a proliferation of languages, concepts and tools that are difficult to govern and are created by users. The semantic web seems to be a natural evolution of the participative web in which we find ourselves, and if an effective combination is achieved between the inclusion of semantic content in web pages and the use of artificial intelligence it will be a revolution; semantic codification will be a fact when it is totally automated. Based on this, a collective digital intelligence is being constituted. We find ourselves before intelligent multitudes with broad access to enormous amounts of information. The intelligent multitude emerges when technologies interconnect. In this global interconnection of semantic information an exponential pattern of technological growth can take place.

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Abstract

The enormous amount of information generated every day and spread across the web is diversified in nature far beyond human consumption. To overcome this difficulty, the transformation of current unstructured information into a structured form called a "Semantic Web" was proposed by Tim Berners-Lee in 1989 to enable computers to understand and interpret the information they store. The aim of the semantic web is the integration of heterogeneous and distributed data spread across the web for knowledge discovery. The core of sematic web technologies includes knowledge representation languages RDF and OWL, ontology editors and reasoning tools, and ontology query languages such as SPARQL have also been discussed.

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Abstract

This book constitutes the refereed proceedings of the 12th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Portoroz, Slovenia, in May/June 2015. The 43 revised full papers presented together with three invited talks were carefully reviewed and selected from 164 submissions. This program was completed by a demonstration and poster session, in which researchers had the chance to present their latest results and advances in the form of live demos. In addition, the PhD Symposium program included 12 contributions, selected out of 16 submissions. The core tracks of the research conference were complemented with new tracks focusing on linking machine and human computation at web scale (cognition and Semantic Web, Human Computation and Crowdsourcing) beside the following subjects Vocabularies, Schemas, Ontologies, Reasoning, Linked Data, Semantic Web and Web Science, Semantic Data Management, Big data, Scalability, Natural Language Processing and Information Retrieval, Machine Learning, Mobile Web, Internet of Things and Semantic Streams, Services, Web APIs and the Web of Things, Cognition and Semantic Web, Human Computation and Crowdsourcing and In-Use Industrial Track as well

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Abstract

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human- and machineconsumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

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Abstract

Many Semantic Web initiatives improve the capabilities of machines to exchange the meaning of information with other machines. These efforts lead to an increased quality of the application's results, but their user interfaces take little or no advantage of the semantic richness. For example, an ontology-based search engine will use its ontology when evaluating the user's query (e.g. for query formulation, disambiguation or evaluation), but fails to use it to significantly enrich the presentation of the results to a human user. For example, one could imagine replacing the endless list of hits with a structured presentation based on the semantic properties of the hits. Another problem is that the modelling of a domain is done from a single perspective (most often that of the information provider). Therefore, presentation based on the resulting ontology is unlikely to satisfy the needs of all the different types of users of the information. So even assuming an ontology for the domain is in place, mapping that ontology to the needs of individual users - based on their tasks, expertise and personal preferences - is not trivial.

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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.

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Abstract

Der Artikel führt in semantische Technologien ein und gewährt Einblick in unterschiedliche Entwicklungsrichtungen. Insbesondere werden Business Semantics vorgestellt und vom Semantic Web abgegrenzt. Die Stärken von Business Semantics werden speziell an den Praxisbeispielen des Knowledge Portals und dem Projekt "Knowledge Base" der Wienerberger AG veranschaulicht. So werden die Anforderungen - was brauchen Anwendungen in Unternehmen heute - und die Leistungsfähigkeit von Systemen - was bieten Business Semantics - konkretisiert und gegenübergestellt.

Source

Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.359-366

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Abstract

Die schnelle Entwicklung der Internet- und Web-Technologie verändert den Stand der Technik in der Kommunikation von Wissen oder Forschungsergebnissen. Insbesondere werden semantische Technologien, verknüpfte und offene Daten zu entscheidenden Faktoren für einen erfolgreichen und effizienten Forschungsfortschritt. Zuerst definiere ich den Research Data Service (RDS) und diskutiere typische aktuelle und mögliche zukünftige Nutzungsszenarien mit RDS. Darüber hinaus bespreche ich den Stand der Technik in den Bereichen semantische Dienstleistung und Datenanmerkung und API-Konstruktion sowie infrastrukturelle Lösungen, die für die RDS-Realisierung anwendbar sind. Zum Schluss werden noch innovative Methoden der Online-Verbreitung, Förderung und effizienten Kommunikation der Forschung diskutiert.

Source

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 70(2017) H.2, S.157-169

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Content

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

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Abstract

Semantic Web ist Vision, Konzept und Programm für die nächste Generation des Internets. Semantik ist dabei ein wesentliches Element in der Transformation von Information in Wissen, sei es um eine effizientere Maschine-Maschine-Kommunikation zu ermöglichen oder um Geschäftsprozess-Management, Wissensmanagement und innerbetriebliche Kooperation durch Modellierung zu verbessern. Der Band richtet sich gleichermaßen an ein praxisorientiertes und wissenschaftliches Publikum, das nicht nur aus der technischen Perspektive einen Zugang zum Thema sucht. Der praktische Nutzen wird in der Fülle von Anwendungsbeispielen offensichtlich, in denen semantische Technologien zum Einsatz kommen. Praxisorientierung ist auch das Leitthema der Semantic Web School, die sich zum Ziel gesetzt hat, den Wissenstransfer zu semantischen Technologien anzukurbeln und den interdisziplinären Diskurs über deren Nutzen und Folgen zu intensivieren. Der vorliegende Band vereinigt 33 Beiträge von 57 Autoren aus 35 Institutionen zu einem virulenten und multidisziplinären Thema. Der Band richtet sich gleichermaßen an interessierte Laien und fachfremde Experten, die nicht nur aus der technischen Perspektive einen Zugang zum Thema suchen. Denn obwohl das Thema Semantic Web zu überwiegendem Maße ein technisches ist, sollen hier bewusst jene Aspekte angesprochen werden. die außerhalb einer ingenieurswissenschaftlichen Perspektive von Relevanz sind und vor allem die praktischen Aspekte semantischer Technologien adressieren. Dieser Anforderung wird durch die vielen Praxisbezüge und Anwendungsbeispiele innerhalb der einzelnen Beiträge Rechnung getragen. Hierbei ist es den Herausgebern jedoch wichtig darauf hinzuweisen, das Semantic Web und semantische Technologien nicht als verheißungsvolles Allheilmittel der durch Informationstechnologien heraufbeschworenen Probleme und Herausforderungen zu betrachten. Ganz im Gegenteil plädieren die Herausgeber für eine verstärkte Auseinandersetzung mit dem Thema unter Einbeziehung einer großen Vielfalt an Experten aus den unterschiedlichsten Fachbereichen, die einen reflektierten und kritischen Beitrag zu den positiven und negativen Effekten semantischer Technologien beitragen sollen.

Content

Inhalt: Im ersten Teil wird neben der begrifflichen Klärung eine Reihe von Einstiegspunkten angeboten, ohne dass der Leser das Semantic Web in seiner Systematik und Funktionsweise kennen muss. Im Beitrag von Andreas Blumauer und Tassilo Pellegrini werden die zentralen Begriffe rund um semantische Technologien vorgestellt und zentrale Konzepte überblicksartig dargestellt. Die Arbeitsgruppe um Bernardi et al. leitet über in den Themenbereich der Arbeitsorganisation und diskutieret die Bedingungen für den Einsatz semantischer Technologien aus der Perspektive der Wissensarbeit. Dem Thema Normen und Standards wurden sogar zwei Beiträge gewidmet. Während Christian Galinski die grundsätzliche Notwendigkeit von Normen zu Zwecken der Interoperabilität aus einer Top-DownPerspektive beleuchtet, eröffnet Klaus Birkenbihl einen Einblick in die technischen Standards des Semantic Web aus der Bottom-Up-Perspektive des World Wide Web Consortiums (W3C). Mit einem Beitrag zum Innovationsgrad semantischer Technologien in der ökonomischen Koordination betreten Michael Weber und Karl Fröschl weitgehend theoretisches Neuland und legen ein Fundament für weiterführende Auseinandersetzungen. Abgerundet wird der erste Teil noch mit einem Beitrag von Bernd Wohlkinger und Tassilo Pellegrini über die technologiepolitischen Dimensionen der Semantic Web Forschung in der europäischen Union.
Im zweiten Teil steht der Anwender des Semantic Web im Mittelpunkt, womit auch die erste Ebene der systematischen Auseinandersetzung mit semantischen Technologien angesprochen wird. Nicola Henze zeigt auf, welchen Beitrag semantische Technologien für die Personalisierung von Informationssystemen leisten. Stefanie Lindstaedt und Armin Ulbrich diskutieren die Möglichkeiten der Zusammenführung von Arbeiten und Lernen zu Zwecken der Kompetenzentwicklung in Arbeitsprozessen. Leo Sauermann stellt daraufhin mit der Metapher des "Semantic Desktop" ein innovatives Konzept für den Arbeitsplatz der Zukunft vor und fragt - nicht ohne eine gewisse Ironie -, ob dieser Arbeitsplatz tatsächlich auf einen physischen Ort begrenzt ist. Mark Buzinkay zeigt aus einer historischen Perspektive, wie semantische Strukturen die Navigation sowohl im Web als auch auf einzelnen Webseiten verändert haben und noch werden. Michael Schuster und Dieter Rappold adressieren die Konvergenz von Social Software und Semantic Web entlang der persönlichen Aneignung von Informationstechnologien zu Zwecken der sozialen Vernetzung. Remo Burkhard plädiert dafür, Wissensvisualisierung als Brückenfunktion zwischen technischer Infrastruktur und Nutzer wahrzunehmen und demonstriert das Potential der Wissensvisualisierung zur zielgruppengerechten Kommunikation komplexer Zusammenhänge. Abschließend zeigt Gabriele Sauberer, welche Informationskompetenzen und Schlüsselqualifikationen in der modernen Informationsgesellschaft von Bedeutung sein werden, in der der Einsatz semantische Technologien zur täglichen Wissensarbeit gehören wird.
Der dritte Teil des Bandes thematisiert die organisationalen Dimensionen des Semantic Web und demonstriert unter dem Stichwort "Wissensmanagement" eine Reihe von Konzepten und Anwendungen im betrieblichen und kollaborativen Umgang mit Information. Der Beitrag von Andreas Blumauer und Thomas Fundneider bietet einen Überblick über den Einsatz semantischer Technologien am Beispiel eines integrierten Wissensmanagement-Systems. Michael John und Jörg Drescher zeichnen den historischen Entwicklungsprozess des IT-Einsatzes für das Management von Informations- und Wissensprozessen im betrieblichen Kontext. Vor dem Hintergrund der betrieblichen Veränderungen durch Globalisierung und angeheizten Wettbewerb zeigt Heiko Beier, welche Rollen, Prozesse und Instrumente in wissensbasierten Organisationen die effiziente Nutzung von Wissen unterstützen. Mit dem Konzept des kollaborativen Wissensmanagement präsentiert das Autorenteam Schmitz et al. einen innovativen WissensmanagementAnsatz auf Peer-to-Peer-Basis mit dem Ziel der kollaborativen Einbindung und Pflege von dezentralisierten Wissensbasen. York Sure und Christoph Tempich demonstrieren anhand der Modellierungsmethode DILIGENT, welchen Beitrag Ontologien bei der Wissensvernetzung in Organisationen leisten können. Hannes Werthner und Michael Borovicka adressieren die Bedeutung semantischer Technologien für eCommerce und demonstrieren am Beispiel HARMONISE deren Einsatz im Bereich des eTourismus. Erweitert wird diese Perspektive durch den Beitrag von Fill et al., in dem das Zusammenspiel zwischen Web-Services und Geschäftsprozessen aus der Perspektive der Wirtschaftsinformatik analysiert wird. Abschließend präsentiert das Autorenteam Angele et al. eine Reihe von realisierten Anwendungen auf Basis semantischer Technologien und identifiziert kritische Faktoren für deren Einsatz.
Im vierten Teil des Bandes stehen die technischen und infrastrukturellen Aspekte im Mittelpunkt des Interesses, die für den Aufbau und Betrieb semantischer Systeme von Relevanz sind. Wolfgang Kienreich und Markus Strohmaier identifizieren die Wissensmodellierung als Basis für den Einsatz semantischer Technologien für das Knowledge Engineering und stellen zwei grundlegende Modellierungsparadigmen vor. Andreas Koller argumentiert, dass die strukturierte Ablage von Content in Content Management Systemen den Lift-Off des Semantic Web stützen wird und zeigt eine Reihe von einfachen Maßnahmen auf, wie CMS Semantic Web tauglich gemacht werden können. Alois Reitbauer gibt einen leicht verständlichen Überblick über technische Fragestellungen der IT-Integration und demonstriert anhand von Beispielen die Vorteile semantischer Technologien gegenüber konventionellen Methoden. Gerald Reif veranschaulicht die Einsatzgebiete und Leistungsfähigkeit der semantischen Annotation und stellt Tools vor, die den Nutzer bei der Dokumentenverschlagwortung unterstützen. Robert Baumgartner stellt die Funktionsweise von Wrappertechnologien zur Extraktion von Daten aus unstrukturierten Dokumenten vor und demonstriert den Nutzen am Beispiel eines B2B-Szenarios. Michael Granitzer bietet einen Überblick über statistische Verfahren der Textanalyse und zeigt, welchen Beitrag diese zur Wartung von Ontologien leisten können.
Gerhard Budin geht auf die zentrale Rolle des Terminologiemanagements bei der Ordnung und Intersubjektivierung komplexer Wissensstrukturen ein und gibt Anleitung für die Entwicklung von terminologischen Metamodellen. Marc Ehrig und Rudi Studer thematisieren Prinzipien und Herausforderungen der semantischen Integration von Ontologien zu Zwecken der Herstellung von Interoperabilität von Web Services. Wolfgang May gibt eine Einführung in das Thema Reasoning im und für das Semantic Web und zeigt auf, welche Mechanismen und Konzepte in naher Zukunft für das Semantic Web relevant werden. Abschließend führt die Autorengruppe um Polleres et al. in das junge Thema der semantischen Beschreibung von Web Services ein und adressiert Fragestellungen der Service Komposition und Automatisierung von Geschäftsprozessen. In einem Nachwort widmet sich Rafael Capurro der Frage, wie es in Zeiten eines auftauchenden semantischen Web um die philosophische Hermeneutik bestellt ist. Und er kommt zu dem Schluss, dass das Semantic Web als ein weltpolitisches Projekt verstanden werden sollte, das zu wichtig ist, um es alleine den Technikern oder den Politikern zu überlassen.

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Abstract

Semantic Web tools provide new and significant opportunities for organizing and improving the utility of biomedical information. As librarians become more involved with biomedical information, it is important for them, particularly catalogers, to be part of research teams that are employing these techniques and developing a high level interoperable biomedical infrastructure. To illustrate these principles, we used Semantic Web tools to create a knowledge model for human visual phenotypes (observable characteristics). This is an important foundation for generating associations between genomics and clinical medicine. In turn this can allow customized medical therapies and provide insights into the molecular basis of disease. The knowledge model incorporates a wide variety of clinical and genomic data including examination findings, demographics, laboratory tests, imaging and variations in DNA sequence. Information organization, storage and retrieval are facilitated through the use of metadata and the ability to make computable statements in the visual science domain. This paper presents our work, discusses the value of Semantic Web technologies in biomedicine, and identifies several important roles that library and information scientists can play in developing a more powerful biomedical information infrastructure.

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Abstract

The DBpedia project is a community effort to extract structured information from Wikipedia and to make this information accessible on the Web. The resulting DBpedia knowledge base currently describes over 2.6 million entities. For each of these entities, DBpedia defines a globally unique identifier that can be dereferenced over the Web into a rich RDF description of the entity, including human-readable definitions in 30 languages, relationships to other resources, classifications in four concept hierarchies, various facts as well as data-level links to other Web data sources describing the entity. Over the last year, an increasing number of data publishers have begun to set data-level links to DBpedia resources, making DBpedia a central interlinking hub for the emerging Web of data. Currently, the Web of interlinked data sources around DBpedia provides approximately 4.7 billion pieces of information and covers domains suc as geographic information, people, companies, films, music, genes, drugs, books, and scientific publications. This article describes the extraction of the DBpedia knowledge base, the current status of interlinking DBpedia with other data sources on the Web, and gives an overview of applications that facilitate the Web of Data around DBpedia.

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Abstract

The World Wide Web as it is currently constituted resembles a poorly mapped geography. Our insight into the documents and capabilities available are based on keyword searches, abetted by clever use of document connectivity and usage patterns. The sheer mass of this data is unmanageable without powerful tool support. In order to map this terrain more precisely, computational agents require machine-readable descriptions of the content and capabilities of Web accessible resources. These descriptions must be in addition to the human-readable versions of that information. The OWL Web Ontology Language is intended to provide a language that can be used to describe the classes and relations between them that are inherent in Web documents and applications. This document demonstrates the use of the OWL language to - formalize a domain by defining classes and properties of those classes, - define individuals and assert properties about them, and - reason about these classes and individuals to the degree permitted by the formal semantics of the OWL language. The sections are organized to present an incremental definition of a set of classes, properties and individuals, beginning with the fundamentals and proceeding to more complex language components.

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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

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Abstract

With the advance of the semantic Web, increasing amounts of data are available in a structured and machine-understandable form. This opens opportunities for users to employ semantic queries instead of simple keyword-based ones to accurately express the information need. However, constructing semantic queries is a demanding task for human users [11]. To compose a valid semantic query, a user has to (1) master a query language (e.g., SPARQL) and (2) acquire sufficient knowledge about the ontology or the schema of the data source. While there are systems which support this task with visual tools [21, 26] or natural language interfaces [3, 13, 14, 18], the process of query construction can still be complex and time consuming. According to [24], users prefer keyword search, and struggle with the construction of semantic queries although being supported with a natural language interface. Several keyword search approaches have already been proposed to ease information seeking on semantic data [16, 32, 35] or databases [1, 31]. However, keyword queries lack the expressivity to precisely describe the user's intent. As a result, ranking can at best put query intentions of the majority on top, making it impossible to take the intentions of all users into consideration.

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Abstract

The Web is a surprisingly extensive source of information: it offers a huge number of sites containing data about a disparate range of topics. Although Web pages are built for human fruition, not for automatic processing of the data, we observe that an increasing number of Web sites deliver pages containing structured information about recognizable concepts, relevant to specific application domains, such as movies, finance, sport, products, etc. The development of scalable techniques to discover, extract, and integrate data from fairly structured large corpora available on the Web is a challenging issue, because to face the Web scale, these activities should be accomplished automatically by domain-independent techniques. To cope with the complexity and the heterogeneity of Web data, state-of-the-art approaches focus on information organized according to specific patterns that frequently occur on the Web. Meaningful examples are WebTables, which focuses on data published in HTML tables, and information extraction systems, such as TextRunner, which exploits lexical-syntactic patterns. As noticed by Cafarella et al., even if a small fraction of the Web is organized according to these patterns, due to the Web scale, the amount of data involved is impressive. In this chapter, we focus on methods and techniques to wring out value from the data delivered by large data-intensive Web sites.