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Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Abstract

Contemporary retrieval systems, which search across collections, usually ignore collection-level metadata. Alternative approaches, exploiting collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection/item metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata creators describing objects, and (iii) system designers implementing systems that take advantage of collection-level metadata. We present three examples of collection/item metadata relationship categories, attribute/value-propagation, value-propagation, and value-constraint and show that even in these simple cases a precise formulation requires modal notions in addition to first-order logic. These formulations are related to recent work in information retrieval and ontology evaluation.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

Graphendatenbanken sind darauf optimiert, stark miteinander vernetzte Informationen effizient zu speichern und greifbar zu machen. Welchen Ansprüchen müssen Abfragesprachen genügen, damit sie für die Arbeit mit diesen Datenbanken geeignet sind? Bei der Aufarbeitung realer Informationen zeigt sich, dass ein hoher, aber unterschätzter Wert in den Beziehungen zwischen Elementen steckt. Seien es Ereignisse aus Geschichte und Politik, Personen in realen und virtuellen sozialen Netzen, Proteine und Gene, Abhängigkeiten in Märkten und Ökonomien oder Rechnernetze, Computer, Software und Anwender - alles ist miteinander verbunden. Der Graph ist ein Datenmodell, das solche Verbindungsgeflechte abbilden kann. Leider lässt sich das Modell mit relationalen und Aggregat-orientierten NoSQL-Datenbanken ab einer gewissen Komplexität jedoch schwer handhaben. Graphendatenbanken sind dagegen darauf optimiert, solche stark miteinander vernetzten Informationen effizient zu speichern und greifbar zu machen. Auch komplexe Fragen lassen sich durch ausgefeilte Abfragen schnell beantworten. Hierbei kommt es auf die geeignete Abfragesprache an.

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Abstract

Purpose Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched. Design/methodology/approach Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson's correlation coefficient and IR measures precision, recall and F-measure. Findings Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed. Originality/value On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.

Date

20. 1.2015 18:30:22

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RSWK

Ontologie <Wissensverarbeitung> / Geoinformationssystem / Semantisches Datenmodell

Subject

Ontologie <Wissensverarbeitung> / Geoinformationssystem / Semantisches Datenmodell

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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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Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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Abstract

Discovering relationships among concepts and categories is crucial in various information systems. The authors' objective was to discover such relationships among document categories. Traditionally, such relationships are represented in the form of a concept hierarchy, grouping some categories under the same parent category. Although the nature of hierarchy supports the identification of categories that may share the same parent, not all of these categories have a relationship with each other - other than sharing the same parent. However, some non-sibling relationships exist that although are related to each other are not identified as such. The authors identify and build a relationship network (relationship-net) with categories as the vertices and relationships as the edges of this network. They demonstrate that using a relationship-net, some nonobvious category relationships are detected. Their approach capitalizes on the misclassification information generated during the process of text classification to identify potential relationships among categories and automatically generate relationship-nets. Their results demonstrate a statistically significant improvement over the current approach by up to 73% on 20 News groups 20NG, up to 68% on 17 categories in the Open Directories Project (ODP17), and more than twice on ODP46 and Special Interest Group on Information Retrieval (SIGIR) data sets. Their results also indicate that using misclassification information stemming from passage classification as opposed to document classification statistically significantly improves the results on 20NG (8%), ODP17 (5%), ODP46 (73%), and SIGIR (117%) with respect to F1 measure. By assigning weights to relationships and by performing feature selection, results are further optimized.

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Content

Topic Maps - Einführung in den ISO Standard (Topics, Associations, Scopes, Facets, Topic Maps).- Grundlagen von XML (Aufbau, Bestandteile, Element- und Attributdefinitionen, DTD, XLink, XPointer).- Wie entsteht ein Heringsschmaus? Konkretes Beispiel einer Topic Map.Topic Maps - Meta DTD. Die formale Beschreibung des Standards.- HyTime als zugrunde liegender Formalismus (Bounded Object Sets, Location Addressing, Hyperlinks in HyTime).- Prototyp eines Topic Map Repositories (Entwicklungsprozess für Topic Maps, Prototyp Spezifikation, technische Realisierung des Prototyps).- Semantisches Datenmodell zur Speicherung von Topic Maps.- Prototypische Abfragesprache für Topic Maps.- Erweiterungsvorschläge für den ISO Standard.

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Abstract

The ISO 2788 guidelines for monolingual thesauri contain a differentiation of "the hierarchical relationship" into "generic", "partitive", and "instance", which, for purposes of document retrieval, was deemed adequate. However, ontologies, designed as language inventories for a wider scope of knowledge representation, are based on all these and some more logical differentiations. Rereading the ISO 2788 standard and inspecting the published Cyc Upper Ontology, it is argued that the adoption of the document-retrieval definition of subsumption generally prevents the conception or use of a thesaurus as a substructure of an ontology of the new kind as constructed for AI applications. When a thesaurus is used for fact description and inference on fact descriptions, the instance-of relationship too should be reconsidered: It may also link concepts and metaconcepts, and then its distinction from subsumption is needed. The treatment of the instance-of relationship in thesauri, the Cyc Upper Ontology, and WordNet is described from this perspective

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Abstract

As part of a larger assessment of relationships in the Dewey Decimal Classification (DDC) system, this study investigates the semantic nature of relationships in the DDC notational hierarchy. The semantic relationship between each of a set of randomly selected classes and its parent class in the notational hierarchy is examined against a set of relationship types (specialization, class-instance, several flavours of whole-part).The analysis addresses the prevalence of specific relationship types, their lexical expression, difficulties encountered in assigning relationship types, compatibility of relationships found in the DDC with those found in other knowledge organization systems (KOS), and compatibility of relationships found in the DDC with those in a shared formalism like the Web Ontology Language (OWL). Since notational hierarchy is an organizational mechanism shared across most classification schemes and is often considered to provide an easy solution for ontological transformation of a classification system, the findings of the study are likely to generalize across classification schemes with respect to difficulties that might be encountered in such a transformation process.

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Abstract

In an ongoing investigation of the relationship between Jason Farradane's relational indexing principles and concept combination in Web-based information on Alzheimer's Disease, the hyperlinks of three consumer health information websites are examined to see how well the linking relationships map to Farradane's relational operators, as well as to the linking attributes in HTML 5. The links were found to be largely bibliographic in nature, and as such mapped well onto HTML 5. Farradane's operators were less effective at capturing the individual links; nonetheless, the two dimensions of his relational matrix-association and discrimination-reveal a crucial underlying strategy of the emotionally-charged mediation between complex information and users who are consulting it under severe stress.

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Abstract

The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.

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Abstract

On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top-k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods.

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Abstract

Topic Maps is an international standard technology for describing knowledge structures and using them to improve the findability of information. It is based on a formal model that subsumes those of traditional finding aids such as indexes, glossaries, and thesauri, and extends them to cater for the additional complexities of digital information. Topic Maps is increasingly used in enterprise information integration, knowledge management, e-learning, and digital libraries, and as the foundation for Web-based information delivery solutions. This entry provides a comprehensive treatment of the core concepts, as well as describing the background and current status of the standard and its relationship to traditional knowledge organization techniques.

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Abstract

Dieser Artikel betrachtet das Problem steigender Komplexität in IT Systemen. Als wesentlicher Aspekt wird Interoperabilität zwischen Anwendungen dargestellt. Als Modell für die Vielschichtigkeit von Integrationszenarien wird ein Modell präsentiert. das Integration und deren Auswirkungen auf verschiedenen Ebenen darstellt. Semantische Technologien werden in Relation zu bestehenden Ansätzen, wie Entity Relationship Diagrammen und objektorientierter Modellierung, gesetzt. Ein konkretes Beispiel demonstriert die unterschiedlichen Modellierungsergebnisse. Als wesentliche Szenarien für die Verwendung von semantischen Technologien werden Daten- und Prozessintegration dargestellt. Hierbei werden zuerst Probleme mit bestehenden Technologien präsentiert. Anschließend folgt anhand von Beispielen die Demonstration, wie semantische Technologien helfen können, diese Probleme zu lösen.

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Abstract

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. This document serves as an introduction to OWL 2 and the various other OWL 2 documents. It describes the syntaxes for OWL 2, the different kinds of semantics, the available profiles (sub-languages), and the relationship between OWL 1 and OWL 2.

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Abstract

This paper is about the relationship between the topic map and RDF standards families. It compares the two technologies and looks at ways to make it easier for users to live in a world where both technologies are used. This is done by looking at how to convert information back and forth between the two technologies, how to convert schema information, and how to do queries across both information representations. Ways to achieve all of these goals are presented. This paper extends and improves on earlier work on the same subject, described in [Garshol01b]. This paper was first published in the proceedings of XML Europe 2003, 5-8 May 2003, organized by IDEAlliance, London, UK.

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Abstract

LCSH is known as such since 1975. It always has created headings to serve the LC collections instead of a theoretical basis. It started to replace cross reference codes by thesaural codes in 1986, in a mechanical fashion. It was in no way transformed into a thesaurus. Its encyclopedic coverage, its pre-coordinate concepts make it substantially distinct, considering that thesauri usually map a restricted field of knowledge and use uniterms. The questions raised are whether the new symbols comply with thesaurus standards and if they are true to one or to several models. Explanations and definitions from other lists of subject headings and thesauri, literature in the field of classification and subject indexing will provide some answers. For instance, see refers from a subject heading not used to another or others used. Exceptionally it will lead from a specific term to a more general one. Some equate a see reference with the equivalence relationship. Such relationships are pointed by USE in LCSH. See also references are made from the broader subject to narrower parts of it and also between associated subjects. They suggest lateral or vertical connexions as well as reciprocal relationships. They serve a coordination purpose for some, lay down a methodical search itinerary for others. Since their inception in the 1950's thesauri have been devised for indexing and retrieving information in the fields of science and technology. Eventually they attended to a number of social sciences and humanities. Research derived from thesauri was voluminous. Numerous guidelines are designed. They did not discriminate between the "hard" sciences and the social sciences. RT relationships are widely but diversely used in numerous controlled vocabularies. LCSH's aim is to achieve a list almost free of RT and SA references. It thus restricts relationships to BT/NT, USE and UF. This raises the question as to whether all fields of knowledge can "fit" in the Procrustean bed of RT/NT, i.e., genus/species relationships. Standard codes were devised. It was soon realized that BT/NT, well suited to the genus/species couple could not signal a whole-part relationship. In LCSH, BT and NT function as reciprocals, the whole-part relationship is taken into account by ISO. It is amply elaborated upon by authors. The part-whole connexion is sometimes studied apart. The decision to replace cross reference codes was an improvement. Relations can now be distinguished through the distinct needs of numerous fields of knowledge are not attended to. Topic inclusion, and topic-subtopic, could provide the missing link where genus/species or whole/part are inadequate. Distinct codes, BT/NT and whole/part, should be provided. Sorting relationships with mechanical means can only lead to confusion.