Search (77 results, page 4 of 4)

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Source

Information processing and management. 45(2009) no.2, S.175-188

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Abstract

An information-seeking system is described which combines traditional keyword querying of WWW resources with the ability to browse and query against RDF annotations of those resources. RDF(S) and RDF are used to specify and populate an ontology and the resultant RDF annotations are then indexed along with the full text of the annotated resources. The resultant index allows both keyword querying against the full text of the document and the literal values occurring in the RDF annotations, along with the ability to browse and query the ontology. We motivate our approach as a key enabler for fully exploiting the Semantic Web in the area of knowledge management and argue that the ability to combine searching and browsing behaviours more fully supports a typical information-seeking task. The approach is characterised as "low threshold, high ceiling" in the sense that where RDF annotations exist they are exploited for an improved information-seeking experience but where they do not yet exist, a search capability is still available.

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Source

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

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Abstract

T.1: Today's thesauri are mostly electronic tools, having moved on from the paper-based era when thesaurus standards were first developed. They are built and maintained with the support of software and need to integrate with other software, such as search engines and content management systems. Whereas in the past thesauri were designed for information professionals trained in indexing and searching, today there is a demand for vocabularies that untrained users will find to be intuitive. ISO 25964 makes the transition needed for the world of electronic information management. However, part 1 retains the assumption that human intellect is usually involved in the selection of indexing terms and in the selection of search terms. If both the indexer and the searcher are guided to choose the same term for the same concept, then relevant documents will be retrieved. This is the main principle underlying thesaurus design, even though a thesaurus built for human users may also be applied in situations where computers make the choices. Efficient exchange of data is a vital component of thesaurus management and exploitation. Hence the inclusion in this standard of recommendations for exchange formats and protocols. Adoption of these will facilitate interoperability between thesaurus management systems and the other computer applications, such as indexing and retrieval systems, that will utilize the data. Thesauri are typically used in post-coordinate retrieval systems, but may also be applied to hierarchical directories, pre-coordinate indexes and classification systems. Increasingly, thesaurus applications need to mesh with others, such as automatic categorization schemes, free-text search systems, etc. Part 2 of ISO 25964 describes additional types of structured vocabulary and gives recommendations to enable interoperation of the vocabularies at all stages of the information storage and retrieval process.

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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

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Date

26. 9.2006 21:00:22

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Source

Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a

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Source

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

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Abstract

The structural and syntactic web put in place in the early 90s is still much the same as what we use today: resources (web pages, files, etc.) connected by untyped hyperlinks. By untyped, we mean that there is no easy way for a computer to figure out what a link between two pages means - for example, on the W3C website, there are hundreds of links to the various organisations that are registered members of the association, but there is nothing explicitly saying that the link is to an organisation that is a "member of" the W3C or what type of organisation is represented by the link. On John's work page, he links to many papers he has written, but it does not explicitly say that he is the author of those papers or that he wrote such-and-such when he was working at a particular university. In fact, the Web was envisaged to be much more, as one can see from the image in Fig. 1 which is taken from Tim Berners Lee's original outline for the Web in 1989, entitled "Information Management: A Proposal". In this, all the resources are connected by links describing the type of relationships, e.g. "wrote", "describe", "refers to", etc. This is a precursor to the Semantic Web which we will come back to later.

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Abstract

An information-seeking system is described which combines traditional keyword querying of WWW resources with the ability to browse and query against RD annotations of those resources. RDF(S) and RDF are used to specify and populate an ontology and the resultant RDF annotations are then indexed along with the full text of the annotated resources. The resultant index allows both keyword querying against the full text of the document and the literal values occurring in the RDF annotations, along with the ability to browse and query the ontology. We motivate our approach as a key enabler for fully exploiting the Semantic Web in the area of knowledge management and argue that the ability to combine searching and browsing behaviours more fully supports a typical information-seeking task. The approach is characterised as "low threshold, high ceiling" in the sense that where RDF annotations exist they are exploited for an improved information-seeking experience but where they do not yet exist, a search capability is still available.

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Source

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

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Abstract

This book constitutes the refereed proceedings of the 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, held in Loughborough, UK in June 2003. The 81 revised full papers presented were carefully reviewed and selected from more than 140 submissions. Among the topics addressed are soft computing, fuzzy logic, diagnosis, knowledge representation, knowledge management, automated reasoning, machine learning, planning and scheduling, evolutionary computation, computer vision, agent systems, algorithmic learning, tutoring systems, financial analysis, etc.

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Series

Advances in information systems and management science; 39

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Abstract

Grounded on a strong belief that ontologies enhance the performance of information retrieval systems, there has been an upsurge of interest in ontologies. Its importance is identified in diverse research fields such as knowledge engineering, knowledge representation, qualitative modeling, language engineering, database design, information integration, object-oriented analysis, information retrieval and extraction, knowledge management and agent-based systems design (Guarino, 1998). While the role-played by ontologies, automatically lends a place of legitimacy for these tools, research in this area gains greater significance in the wake of various challenges faced in the contemporary digital environment. With the objective of overcoming various pitfalls associated with current search mechanisms, ontologies are increasingly used for developing efficient information retrieval systems. An indicator of research interest in the area of ontology is the Swoogle, a search engine for Semantic Web documents, terms and data found on the Web (Ding, Li et al, 2004). Given the complex nature of the digital content archived in digital libraries, ontologies can be employed for designing efficient forms of information retrieval in digital libraries. Knowledge representation assumes greater significance due to its crucial role in ontology development. These systems aid in developing intelligent information systems, wherein the notion of intelligence implies the ability of the system to find implicit consequences of its explicitly represented knowledge (Baader and Nutt, 2003). Knowledge representation formalisms such as 'Description Logics' are used to obtain explicit knowledge representation of the subject domain. These representations are developed into ontologies, which are used for developing intelligent information systems. Against this backdrop, the paper examines the use of Description Logics for conceptually modeling a chosen domain, which would be utilized for developing domain ontologies. The knowledge representation languages identified for this purpose are Web Ontology Language (OWL) and KArlsruhe ONtology (KAON) language. Drawing upon the various technical constructs in developing ontology-based information systems, the paper explains the working of the prototypes and also presents a comparative study of the two prototypes.

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Source

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

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Abstract

Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.

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Content

Short Papers * A Database Backend for OWL, Jörg Henss, Joachim Kleb and Stephan Grimm. * Unifying SysML and OWL, Henson Graves. * The OWLlink Protocol, Thorsten Liebig, Marko Luther and Olaf Noppens. * A Reasoning Broker Framework for OWL, Juergen Bock, Tuvshintur Tserendorj, Yongchun Xu, Jens Wissmann and Stephan Grimm. * Change Representation For OWL 2 Ontologies, Raul Palma, Peter Haase, Oscar Corcho and Asunción Gómez-Pérez. * Practical Aspects of Query Rewriting for OWL 2, Héctor Pérez-Urbina, Ian Horrocks and Boris Motik. * CSage: Use of a Configurable Semantically Attributed Graph Editor as Framework for Editing and Visualization, Lawrence Levin. * A Conformance Test Suite for the OWL 2 RL/RDF Rules Language and the OWL 2 RDF-Based Semantics, Michael Schneider and Kai Mainzer. * Improving the Data Quality of Relational Databases using OBDA and OWL 2 QL, Olivier Cure. * Temporal Classes and OWL, Natalya Keberle. * Using Ontologies for Medical Image Retrieval - An Experiment, Jasmin Opitz, Bijan Parsia and Ulrike Sattler. * Task Representation and Retrieval in an Ontology-Guided Modelling System, Yuan Ren, Jens Lemcke, Andreas Friesen, Tirdad Rahmani, Srdjan Zivkovic, Boris Gregorcic, Andreas Bartho, Yuting Zhao and Jeff Z. Pan. * A platform for reasoning with OWL-EL knowledge bases in a Peer-to-Peer environment, Alexander De Leon and Michel Dumontier. * Axiomé: a Tool for the Elicitation and Management of SWRL Rules, Saeed Hassanpour, Martin O'Connor and Amar Das. * SQWRL: A Query Language for OWL, Martin O'Connor and Amar Das. * Classifying ELH Ontologies In SQL Databases, Vincent Delaitre and Yevgeny Kazakov. * A Semantic Web Approach to Represent and Retrieve Information in a Corporate Memory, Ana B. Rios-Alvarado, R. Carolina Medina-Ramirez and Ricardo Marcelin-Jimenez. * Towards a Graphical Notation for OWL 2, Elisa Kendall, Roy Bell, Roger Burkhart, Mark Dutra and Evan Wallace.