Search (31 results, page 1 of 2)

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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.

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Abstract

The paper presents the possibilities offered by poly-hierarchical conceptual structures as knowledge organizers, starting from the FRBR entity-relation model. Of the ten entities defined in the FRBR model, the first six, the bibliographic entities plus those representing the intellectual responsibilities, are clearly described by their attributes. Unlike those the other four representing subjects in their own right: concepts, objects, events and places only have the term for the entity as attribute. Subjects have to be more extensively treated in a revised version of the FRBR model, with particular attention for the semantic and syntactic relations between concepts representing subjects themselves and between these concepts and terms used in indexing. The conceptual model of poly-hierarchical thesauri is regarded as an entity-relation model, one capable to accommodate both conceptually and relationally subjects in the bibliographic universe. Polyhierarchical thesauri are considered as frameworks or templates meant to enhance knowledge representation and to support information searching.

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Abstract

The initial research on semantic digital libraries resulted in the design and implementation of JeromeDL; current research on online social networking and information discovery delivered new sets of features that were implemented in JeromeDL. Eventually, this digital library has been redesigned to follow the architecture of a social semantic digital library. JeromeDL describes each resource using three types of metadata: structure, bibliographic and community. It delivers services leveraging each of these information types. Annotations based on the structure and legacy metadata, and bibliographic ontology are rendered to the users in one, mixed, representation of library resources. Community annotations are managed by separate services, such as social semantic collaborative filtering or blogging component

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Content

The paper describes current work on the generation of a thesaurus format from the schedules of the Bliss Bibliographic Classification 2nd edition (BC2). The practical problems that occur in moving from a concept based approach to a terminological approach cluster around issues of vocabulary control that are not fully addressed in a systematic structure. These difficulties can be exacerbated within domains in the humanities because large numbers of culture specific terms may need to be accommodated in any thesaurus. The ways in which these problems can be resolved within the context of a semi-automated approach to the thesaurus generation have consequences for the management of classification data in the source vocabulary. The way in which the vocabulary is marked up for the purpose of machine manipulation is described, and some of the implications for editorial policy are discussed and examples given. The value of the classification notation as a language independent representation and mapping tool should not be sacrificed in such an exercise.

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Date

26.12.2011 13:22:07

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Date

30. 5.2010 16:22:35

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Content

Inhalt: Introduction to Digital Libraries and Semantic Web: Introduction / Bill McDaniel and Sebastian Ryszard Kruk - Digital Libraries and Knowledge Organization / Dagobert Soergel - Semantic Web and Ontologies / Marcin Synak, Maciej Dabrowski and Sebastian Ryszard Kruk - Social Semantic Information Spaces / John G. Breslin A Vision of Semantic Digital Libraries: Goals of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel - Architecture of Semantic Digital Libraries / Sebastian Ryszard Kruk, Adam Westerki and Ewelina Kruk - Long-time Preservation / Markus Reis Ontologies for Semantic Digital Libraries: Bibliographic Ontology / Maciej Dabrowski, Macin Synak and Sebastian Ryszard Kruk - Community-aware Ontologies / Slawomir Grzonkowski, Sebastian Ryszard Kruk, Adam Gzella, Jakub Demczuk and Bill McDaniel Prototypes of Semantic Digital Libraries: JeromeDL: The Social Semantic Digital Library / Sebastian Ryszard Kruk, Mariusz Cygan, Adam Gzella, Tomasz Woroniecki and Maciej Dabrowski - The BRICKS Digital Library Infrastructure / Bernhard Haslhofer and Predrag Knezevié - Semantics in Greenstone / Annika Hinze, George Buchanan, David Bainbridge and Ian Witten Building the Future - Semantic Digital Libraries in Use: Hyperbooks / Gilles Falquet, Luka Nerima and Jean-Claude Ziswiler - Semantic Digital Libraries for Archiving / Bill McDaniel - Evaluation of Semantic and Social Technologies for Digital Libraries / Sebastian Ryszard Kruk, Ewelina Kruk and Katarzyna Stankiewicz - Conclusions: The Future of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel

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Abstract

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.

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Abstract

As information becomes richer and more complex, alternative information-organization methods are needed to more effectively and efficiently retrieve information from various systems, including the Web. The objective of this study is to explore how a Topic Maps-based ontology approach affects users' searching performance. Forty participants participated in a task-based evaluation where two dependent variables, recall and search time, were measured. The results of this study indicate that a Topic Maps-based ontology information retrieval (TOIR) system has a significant and positive effect on both recall and search time, compared to a thesaurus-based information retrieval (TIR) system. These results suggest that the inclusion of a Topic Maps-based ontology is a beneficial approach to take when designing information retrieval systems.

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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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Abstract

This paper presents a novel hybrid approach for visual information retrieval (VIR) that combines shape analysis of objects in image with their indexing by textual descriptions. The principal goal of presented technique is applying Two Segments Turning Function (2STF) proposed by authors for efficient invariant to spatial variations shape processing and implementation of semantic Web approaches for ontology-based user-oriented annotations of multimedia information. In the proposed approach the user's textual queries are converted to image features, which are used for images searching, indexing, interpretation, and retrieval. A decision about similarity between retrieved image and user's query is taken computing the shape convergence to 2STF combining it with matching the ontological annotations of objects in image and providing in this way automatic definition of the machine-understandable semantics. In order to evaluate the proposed approach the Image Retrieval by Ontological Description of Shapes system has been designed and tested using some standard image domains.

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Date

31. 7.2010 16:58:22

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Date

14. 8.2011 13:33:22

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Date

22. 1.2016 17:47:06

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Date

11. 2.2011 18:22:58

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Date

11. 2.2011 18:22:25

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Abstract

Aimed at students and professionals within Library and Information Services (LIS), this book is about the power and potential of ontologies to enhance the electronic search process. The book will compare search strategies and results in the current search environment and demonstrate how these could be transformed using ontologies and concept searching. Simple descriptions, visual representations, and examples of ontologies will bring a full understanding of how these concept maps are constructed to enhance retrieval through natural language queries. Readers will gain a sense of how ontologies are currently being used and how they could be applied in the future, encouraging them to think about how their own work and their users' search experiences could be enhanced by the creation of a customized ontology. Key Features Written by a librarian, for librarians (most work on ontologies is written and read by people in computer science and knowledge management) Written by a librarian who has created her own ontology and performed research on its capabilities Written in easily understandable language, with concepts broken down to the basics The Author Ms. King is the Information Specialist at the Center on Media and Child Health at Children's Hospital Boston. She is a graduate of Smith College (B.A.) and Simmons College (M.L.I.S.). She is an active member of the Special Libraries Association, and was the recipient of the 2005 SLA Innovation in Technology Award for the creation of a customized media effects ontology used for semantic searching. Readership The book is aimed at practicing librarians and information professionals as well as graduate students of Library and Information Science. Contents Introduction Part 1: Understanding Ontologies - organising knowledge; what is an ontology? How are ontologies different from other knowledge representations? How are ontologies currently being used? Key concepts Ontologies in semantic search - determining whether a search was successful; what does semantic search have to offer? Semantic techniques; semantic searching behind the scenes; key concepts Creating an ontology - how to create an ontology; key concepts Building an ontology from existing components - choosing components; customizing your knowledge structure; key concepts Part 2: Semantic Technologies Natural language processing - tagging parts of speech; grammar-based NLP; statistical NLP; semantic analysis,; current applications of NLP; key concepts Using metadata to add semantic information - structured languages; metadata tagging; semantic tagging; key concepts Other semantic capabilities - semantic classification; synsets; topic maps; rules and inference; key concepts Part 3: Case Studies: Theory into Practice Biogen Idec: using semantics in drug discovery research - Biogen Idec's solution; the future The Center on Media and Child Health: using an ontology to explore the effects of media - building the ontology; choosing the source; implementing and comparing to Boolean search; the future Partners HealthCare System: semantic technologies to improve clinical decision support - the medical appointment; partners healthcare system's solution; lessons learned; the future MINDSWAP: using ontologies to aid terrorism; intelligence gathering - building, using and maintaining the ontology; sharing information with other experts; future plans Part 4: Advanced Topics Languages for expressing ontologies - XML; RDF; OWL; SKOS; Ontology language features - comparison chart Tools for building ontologies - basic criteria when evaluating ontologies Part 5: Transitions to the Future

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Abstract

This publication shows how the gap between the HTML based internet and the RDF based vision of the semantic web might be bridged, by linking words in texts to concepts of ontologies. Most current search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. However, the indexes do not contain synonyms, cannot differentiate between homonyms ('mouse' as a pointing vs. 'mouse' as an animal) and users receive different search results when they use different conjugation forms of the same word. In this publication, we present a system that uses ontologies and Natural Language Processing techniques to index texts, and thus supports word sense disambiguation and the retrieval of texts that contain equivalent words, by indexing them to concepts of ontologies. For this purpose, we developed fully automated methods for mapping equivalent concepts of imported RDF ontologies (for this prototype WordNet, SUMO and OpenCyc). These methods will thus allow the seamless integration of domain specific ontologies for concept based information retrieval in different domains. To demonstrate the practical workability of this approach, a set of web pages that contain synonyms and homonyms were indexed and can be queried via a search engine like query frontend. However, the ontology based indexing approach can also be used for other data mining applications such text clustering, relation mining and for searching free text fields in biological databases. The ontology alignment methods and some of the text mining principles described in this publication are now incorporated into the ONDEX system http://ondex.sourceforge.net/.

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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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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.