Search (18 results, page 1 of 1)

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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

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Abstract

Momentan verbreitete Methoden zur Strukturierung von Information können ihre Aufgabe immer schlechter befriedigend erfüllen. Der Grund dafür ist das explosive Wachstum menschlichen Wissens. Diese Diplomarbeit schlägt als einen möglichen Ausweg die Verwendung assoziativer semantischer Netzwerke vor. Maschinelles Wissensmanagement kann wesentlich intuitiver und einfacher benutzbar werden, wenn man sich die Art und Weise zunutze macht, mit der das menschliche Gehirn Informationen verarbeitet (im Speziellen assoziative Verbindungen). Der theoretische Teil dieser Arbeit diskutiert verschiedene Aspekte eines möglichen Designs eines semantischen Netzwerks mit assoziativen Verbindungen. Außer den Grundelementen und Problemen der Visualisierung werden hauptsächlich Verbesserungen ausgearbeitet, welche ein leistungsstarkes Arbeiten mit einem solchen Netzwerk erlauben. Im praktischen Teil wird ein Netzwerk-Prototyp mit den wichtigsten herausgearbeiteten Merkmalen implementiert. Die Basis der Applikation bildet der Hyperwave Information Server. Dieser detailiiertere Design-Teil gewährt tieferen Einblick in Software Requirements, Use Cases und teilweise auch in Klassendetails. Am Ende wird eine kurze Einführung in die Benutzung des implementierten Prototypen gegeben.

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Abstract

In der globalen Online-Umgebung stellen viele bibliographische Dienstleistungen integrierten Zugang zu unterschiedlichen internetbasierten OPACs zur Verfügung. In solch einer Umgebung erwarten Benutzer mehr Übereinstimmungen innerhalb und zwischen den Systemen zu sehen. Zweck dieser Studie ist, die Indexierungskonsistenz zwischen Systemen zu untersuchen. Währenddessen werden einige Faktoren, die die Indexierungskonsistenz beeinflussen können, untersucht. Wichtigstes Ziel dieser Studie ist, die Gründe für die Inkonsistenzen herauszufinden, damit sinnvolle Vorschläge gemacht werden können, um die Indexierungskonsistenz zu verbessern. Eine Auswahl von 3307 Monographien wurde aus zwei chinesischen bibliographischen Katalogen gewählt. Nach Hooper's Formel war die durchschnittliche Indexierungskonsistenz für Indexterme 64,2% und für Klassennummern 61,6%. Nach Rolling's Formel war sie für Indexterme 70,7% und für Klassennummern 63,4%. Mehrere Faktoren, die die Indexierungskonsistenz beeinflussen, wurden untersucht: (1) Indexierungsbereite; (2) Indexierungsspezifizität; (3) Länge der Monographien; (4) Kategorie der Indexierungssprache; (5) Sachgebiet der Monographien; (6) Entwicklung von Disziplinen; (7) Struktur des Thesaurus oder der Klassifikation; (8) Erscheinungsjahr. Gründe für die Inkonsistenzen wurden ebenfalls analysiert. Die Analyse ergab: (1) den Indexieren mangelt es an Fachwissen, Vertrautheit mit den Indexierungssprachen und den Indexierungsregeln, so dass viele Inkonsistenzen verursacht wurden; (2) der Mangel an vereinheitlichten oder präzisen Regeln brachte ebenfalls Inkonsistenzen hervor; (3) verzögerte Überarbeitungen der Indexierungssprachen, Mangel an terminologischer Kontrolle, zu wenige Erläuterungen und "siehe auch" Referenzen, sowie die hohe semantische Freiheit bei der Auswahl von Deskriptoren oder Klassen, verursachten Inkonsistenzen.

Imprint

Berlin : Humboldt-Universität / Institut für Bibliotheks- und Informationswissenschaft

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Footnote

Rez. in: ABI-Technik 21(2002) H.3, S.292 (E. Pietzsch): "Otto C. Oberhauser hat mit seiner Diplomarbeit eine beeindruckende Analyse digitalisierter Zettelkataloge (CIPACs) vorgelegt. Die Arbeit wartet mit einer Fülle von Daten und Statistiken auf, wie sie bislang nicht vorgelegen haben. BibliothekarInnen, die sich mit der Digitalisierung von Katalogen tragen, finden darin eine einzigartige Vorlage zur Entscheidungsfindung. Nach einem einführenden Kapitel bringt Oberhauser zunächst einen Überblick über eine Auswahl weltweit verfügbarer CIPACs, deren Indexierungsmethode (Binäre Suche, partielle Indexierung, Suche in OCR-Daten) und stellt vergleichende Betrachtungen über geographische Verteilung, Größe, Software, Navigation und andere Eigenschaften an. Anschließend beschreibt und analysiert er Implementierungsprobleme, beginnend bei Gründen, die zur Digitalisierung führen können: Kosten, Umsetzungsdauer, Zugriffsverbesserung, Stellplatzersparnis. Er fährt fort mit technischen Aspekten wie Scannen und Qualitätskontrolle, Image Standards, OCR, manueller Nacharbeit, Servertechnologie. Dabei geht er auch auf die eher hinderlichen Eigenschaften älterer Kataloge ein sowie auf die Präsentation im Web und die Anbindung an vorhandene Opacs. Einem wichtigen Aspekt, nämlich der Beurteilung durch die wichtigste Zielgruppe, die BibliotheksbenutzerInnen, hat Oberhauser eine eigene Feldforschung gewidmet, deren Ergebnisse er im letzten Kapitel eingehend analysiert. Anhänge über die Art der Datenerhebung und Einzelbeschreibung vieler Kataloge runden die Arbeit ab. Insgesamt kann ich die Arbeit nur als die eindrucksvollste Sammlung von Daten, Statistiken und Analysen zum Thema CIPACs bezeichnen, die mir bislang begegnet ist. Auf einen schön herausgearbeiteten Einzelaspekt, nämlich die weitgehende Zersplitterung bei den eingesetzten Softwaresystemen, will ich besonders eingehen: Derzeit können wir grob zwischen Komplettlösungen (eine beauftragte Firma führt als Generalunternehmung sämtliche Aufgaben von der Digitalisierung bis zur Ablieferung der fertigen Anwendung aus) und geteilten Lösungen (die Digitalisierung wird getrennt von der Indexierung und der Softwareerstellung vergeben bzw. im eigenen Hause vorgenommen) unterscheiden. Letztere setzen ein Projektmanagement im Hause voraus. Gerade die Softwareerstellung im eigenen Haus aber kann zu Lösungen führen, die kommerziellen Angeboten keineswegs nachstehen. Schade ist nur, daß die vielfältigen Eigenentwicklungen bislang noch nicht zu Initiativen geführt haben, die, ähnlich wie bei Public Domain Software, eine "optimale", kostengünstige und weithin akzeptierte Softwarelösung zum Ziel haben. Einige kritische Anmerkungen sollen dennoch nicht unerwähnt bleiben. Beispielsweise fehlt eine Differenzierung zwischen "Reiterkarten"-Systemen, d.h. solchen mit Indexierung jeder 20. oder 50. Karte, und Systemen mit vollständiger Indexierung sämtlicher Kartenköpfe, führt doch diese weitreichende Designentscheidung zu erheblichen Kostenverschiebungen zwischen Katalogerstellung und späterer Benutzung. Auch bei den statistischen Auswertungen der Feldforschung hätte ich mir eine feinere Differenzierung nach Typ des CIPAC oder nach Bibliothek gewünscht. So haben beispielsweise mehr als die Hälfte der befragten BenutzerInnen angegeben, die Bedienung des CIPAC sei zunächst schwer verständlich oder seine Benutzung sei zeitaufwendig gewesen. Offen beibt jedoch, ob es Unterschiede zwischen den verschiedenen Realisierungstypen gibt.
Nun haben Diplomarbeiten einen eigenen Charakter. Ihre Zielsetzung ist nicht unbedingt, Handlungsleitfäden zu geben. Manche FachkollegInnen, die schon selbst mit der Digitalisierung von Katalogen zu tun hatten, fragen sich aber, ob die jeweils gefundene Lösung denn tatsächlich die "beste" erreichbare war, ob es sich lohnt, über Verbesserungen nachzudenken, wie ihre Lösung im Vergleich zu anderen steht, ob die eingesetzte Recherchesoftware gute Ergebnisse liefert, ob die zunächst vielleicht niedrigen Erstellungskosten nicht doch relativ lange Verweildauern, d.h. verdeckte Kosten, bei der Recherche zur Folge haben. Oberhauser gibt dazu lediglich am Rande einige Hinweise. Wünschenswert wäre, wenn derartige Detailuntersuchungen in weiteren Arbeiten vorgenommen würden."

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Abstract

The use of thesaurus-based indexing is a common approach for increasing the performance of information retrieval. In this thesis, we examine the suitability of a thesaurus for a given set of information and evaluate improvements of existing thesauri to get better search results. On this area, we focus on two aspects: 1. We demonstrate an analysis of the indexing results achieved by an automatic document indexer and the involved thesaurus. 2. We propose a method for thesaurus evaluation which is based on a combination of statistical measures and appropriate visualization techniques that support the detection of potential problems in a thesaurus. In this chapter, we give an overview of the context of our work. Next, we briefly outline the basics of thesaurus-based information retrieval and describe the Collexis Engine that was used for our experiments. In Chapter 3, we describe two experiments in automatically indexing documents in the areas of medicine and economics with corresponding thesauri and compare the results to available manual annotations. Chapter 4 describes methods for assessing thesauri and visualizing the result in terms of a treemap. We depict examples of interesting observations supported by the method and show that we actually find critical problems. We conclude with a discussion of open questions and future research in Chapter 5.

Imprint

Mannheim : Fakultät für Mathematik und Informatik

Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Abstract

The integration of metadata from distinct, heterogeneous data sources requires metadata interoperability, which is a qualitative property of metadata information objects that is not given by default. The technique of metadata mapping allows domain experts to establish metadata interoperability in a certain integration scenario. Mapping solutions, as a technical manifestation of this technique, are already available for the intensively studied domain of database system interoperability, but they rarely exist for the Web. If we consider the amount of steadily increasing structured metadata and corresponding metadata schemes on theWeb, we can observe a clear need for a mapping solution that can operate in aWeb-based environment. To achieve that, we first need to build its technical core, which is a mapping model that provides the language primitives to define mapping relationships. Existing SemanticWeb languages such as RDFS and OWL define some basic mapping elements (e.g., owl:equivalentProperty, owl:sameAs), but do not address the full spectrum of semantic and structural heterogeneities that can occur among distinct, incompatible metadata information objects. Furthermore, it is still unclear how to process defined mapping relationships during run-time in order to deliver metadata to the client in a uniform way. As the main contribution of this thesis, we present an abstract mapping model, which reflects the mapping problem on a generic level and provides the means for reconciling incompatible metadata. Instance transformation functions and URIs take a central role in that model. The former cover a broad spectrum of possible structural and semantic heterogeneities, while the latter bind the complete mapping model to the architecture of the Word Wide Web. On the concrete, language-specific level we present a binding of the abstract mapping model for the RDF Vocabulary Description Language (RDFS), which allows us to create mapping specifications among incompatible metadata schemes expressed in RDFS. The mapping model is embedded in a cyclic process that categorises the requirements a mapping solution should fulfil into four subsequent phases: mapping discovery, mapping representation, mapping execution, and mapping maintenance. In this thesis, we mainly focus on mapping representation and on the transformation of mapping specifications into executable SPARQL queries. For mapping discovery support, the model provides an interface for plugging-in schema and ontology matching algorithms. For mapping maintenance we introduce the concept of a simple, but effective mapping registry. Based on the mapping model, we propose aWeb-based mediator wrapper-architecture that allows domain experts to set up mediation endpoints that provide a uniform SPARQL query interface to a set of distributed metadata sources. The involved data sources are encapsulated by wrapper components that expose the contained metadata and the schema definitions on the Web and provide a SPARQL query interface to these metadata. In this thesis, we present the OAI2LOD Server, a wrapper component for integrating metadata that are accessible via the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). In a case study, we demonstrate how mappings can be created in aWeb environment and how our mediator wrapper architecture can easily be configured in order to integrate metadata from various heterogeneous data sources without the need to install any mapping solution or metadata integration solution in a local system environment.

Content

Die Integration von Metadaten aus unterschiedlichen, heterogenen Datenquellen erfordert Metadaten-Interoperabilität, eine Eigenschaft die nicht standardmäßig gegeben ist. Metadaten Mapping Verfahren ermöglichen es Domänenexperten Metadaten-Interoperabilität in einem bestimmten Integrationskontext herzustellen. Mapping Lösungen sollen dabei die notwendige Unterstützung bieten. Während diese für den etablierten Bereich interoperabler Datenbanken bereits existieren, ist dies für Web-Umgebungen nicht der Fall. Betrachtet man das Ausmaß ständig wachsender strukturierter Metadaten und Metadatenschemata im Web, so zeichnet sich ein Bedarf nach Web-basierten Mapping Lösungen ab. Den Kern einer solchen Lösung bildet ein Mappingmodell, das die zur Spezifikation von Mappings notwendigen Sprachkonstrukte definiert. Existierende Semantic Web Sprachen wie beispielsweise RDFS oder OWL bieten zwar grundlegende Mappingelemente (z.B.: owl:equivalentProperty, owl:sameAs), adressieren jedoch nicht das gesamte Sprektrum möglicher semantischer und struktureller Heterogenitäten, die zwischen unterschiedlichen, inkompatiblen Metadatenobjekten auftreten können. Außerdem fehlen technische Lösungsansätze zur Überführung zuvor definierter Mappings in ausfu¨hrbare Abfragen. Als zentraler wissenschaftlicher Beitrag dieser Dissertation, wird ein abstraktes Mappingmodell pr¨asentiert, welches das Mappingproblem auf generischer Ebene reflektiert und Lösungsansätze zum Abgleich inkompatibler Schemata bietet. Instanztransformationsfunktionen und URIs nehmen in diesem Modell eine zentrale Rolle ein. Erstere überbrücken ein breites Spektrum möglicher semantischer und struktureller Heterogenitäten, während letztere das Mappingmodell in die Architektur des World Wide Webs einbinden. Auf einer konkreten, sprachspezifischen Ebene wird die Anbindung des abstrakten Modells an die RDF Vocabulary Description Language (RDFS) präsentiert, wodurch ein Mapping zwischen unterschiedlichen, in RDFS ausgedrückten Metadatenschemata ermöglicht wird. Das Mappingmodell ist in einen zyklischen Mappingprozess eingebunden, der die Anforderungen an Mappinglösungen in vier aufeinanderfolgende Phasen kategorisiert: mapping discovery, mapping representation, mapping execution und mapping maintenance. Im Rahmen dieser Dissertation beschäftigen wir uns hauptsächlich mit der Representation-Phase sowie mit der Transformation von Mappingspezifikationen in ausführbare SPARQL-Abfragen. Zur Unterstützung der Discovery-Phase bietet das Mappingmodell eine Schnittstelle zur Einbindung von Schema- oder Ontologymatching-Algorithmen. Für die Maintenance-Phase präsentieren wir ein einfaches, aber seinen Zweck erfüllendes Mapping-Registry Konzept. Auf Basis des Mappingmodells stellen wir eine Web-basierte Mediator-Wrapper Architektur vor, die Domänenexperten die Möglichkeit bietet, SPARQL-Mediationsschnittstellen zu definieren. Die zu integrierenden Datenquellen müssen dafür durch Wrapper-Komponenen gekapselt werden, welche die enthaltenen Metadaten im Web exponieren und SPARQL-Zugriff ermöglichen. Als beipielhafte Wrapper Komponente präsentieren wir den OAI2LOD Server, mit dessen Hilfe Datenquellen eingebunden werden können, die ihre Metadaten über das Open Archives Initative Protocol for Metadata Harvesting (OAI-PMH) exponieren. Im Rahmen einer Fallstudie zeigen wir, wie Mappings in Web-Umgebungen erstellt werden können und wie unsere Mediator-Wrapper Architektur nach wenigen, einfachen Konfigurationsschritten Metadaten aus unterschiedlichen, heterogenen Datenquellen integrieren kann, ohne dass dadurch die Notwendigkeit entsteht, eine Mapping Lösung in einer lokalen Systemumgebung zu installieren.

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Abstract

The past decade has seen the emergence of a new paradigm in the corporate world where organisations emphasised connectivity as a means of exposing decision-makers to wider resources of information within and outside the organisation. Many organisations followed the initiatives of enhancing infrastructures, manipulating cultural shifts and emphasising managerial commitment for creating pools and networks of knowledge. However, the concept of connectivity is not merely presenting people with the data, but more importantly, to create environments where people can seek information efficiently. This paradigm has therefore caused a shift in the function of information systems in organisations. They have to be now assessed in relation to how they underpin people's information-seeking activities within the context of their organisational environment. This research project used interpretative research methods to investigate the nature of people's information-seeking activities at two culturally contrasting organisations. Outcomes of this research project provide insights into phenomena associated with people's information-seeking function, and show how they depend on the organisational context that is defined partly by information systems. It suggests that information-seeking is not just searching for data. The inefficiencies inherent in both people and their environments can bring opaqueness into people's data, which they need to avoid or eliminate as part of seeking information. This seems to have made information-seeking a two-tier process consisting of a primary process of searching and interpreting data and auxiliary process of avoiding and eliminating opaqueness in data. Based on this view, this research suggests that organisational information systems operate naturally as implicit dual-mechanisms to underpin the above two-tier process, and that improvements to information systems should concern maintaining the balance in these dual-mechanisms.

Date

22. 7.2022 12:16:58

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Abstract

This work proposes an approach which is intended to meet the particular challenges of Medical Language Processing, in particular medical information retrieval. At its core lies a new type of dictionary, in which the entries are equivalence classes of subwords, i.e., semantically minimal units. These equivalence classes capture intralingual as well as interlingual synonymy. As equivalence classes abstract away from subtle particularities within and between languages and reference to them is realized via a language-independent conceptual system, they form an interlingua. In this work, the theoretical foundations of this approach are elaborated on. Furthermore, design considerations of applications based on the subword methodology are drawn up and showcase implementations are evaluated in detail. Starting with the introduction of Medical Linguistics as a field of active research in Chapter two, its consideration as a domain separated form general linguistics is motivated. In particular, morphological phenomena inherent to medical language are figured in more detail, which leads to an alternative view on medical terms and the introduction of the notion of subwords. Chapter three describes the formal foundation of subwords and the underlying linguistic declarative as well as procedural knowledge. An implementation of the subword model for the medical domain, the MorphoSaurus system, is presented in Chapter four. Emphasis will be given on the multilingual aspect of the proposed approach, including English, German, and Portuguese. The automatic acquisition of (medical) subwords for other languages (Spanish, French, and Swedish), and their integration in already available resources is described in the fifth Chapter.
The proper handling of acronyms plays a crucial role in medical texts, e.g. in patient records, as well as in scientific literature. Chapter six presents an approach, in which acronyms are automatically acquired from (bio-) medical literature. Furthermore, acronyms and their definitions in different languages are linked to each other using the MorphoSaurus text processing system. Automatic word sense disambiguation is still one of the most challenging tasks in Natural Language Processing. In Chapter seven, cross-lingual considerations lead to a new methodology for automatic disambiguation applied to subwords. Beginning with Chapter eight, a series of applications based onMorphoSaurus are introduced. Firstly, the implementation of the subword approach within a crosslanguage information retrieval setting for the medical domain is described and evaluated on standard test document collections. In Chapter nine, this methodology is extended to multilingual information retrieval in the Web, for which user queries are translated into target languages based on the segmentation into subwords and their interlingual mappings. The cross-lingual, automatic assignment of document descriptors to documents is the topic of Chapter ten. A large-scale evaluation of a heuristic, as well as a statistical algorithm is carried out using a prominent medical thesaurus as a controlled vocabulary. In Chapter eleven, it will be shown how MorphoSaurus can be used to map monolingual, lexical resources across different languages. As a result, a large multilingual medical lexicon with high coverage and complete lexical information is built and evaluated against a comparable, already available and commonly used lexical repository for the medical domain. Chapter twelve sketches a few applications based on MorphoSaurus. The generality and applicability of the subword approach to other domains is outlined, and proof-of-concepts in real-world scenarios are presented. Finally, Chapter thirteen recapitulates the most important aspects of MorphoSaurus and the potential benefit of its employment in medical information systems is carefully assessed, both for medical experts in their everyday life, but also with regard to health care consumers and their existential information needs.

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Abstract

In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun phrases. Furthermore, we briefly cover the identification of semantic relations inside and between noun phrases, as well as discuss which kind of problems are caused by an increase in compoundness with respect to the structure of concepts in the evaluation of queries. Measuring similarity between concepts based on distances in the structure of the ontology is discussed. In addition, a shared nodes measure is introduced and, based on a set of intuitive similarity properties, compared to a number of different measures. In this comparison the shared nodes measure appears to be superior, though more computationally complex. Some of the major problems of shared nodes which relate to the way relations differ with respect to the degree they bring the concepts they connect closer are discussed. A generalized measure called weighted shared nodes is introduced to deal with these problems. Finally, the utilization of concept similarity in query evaluation is discussed. A semantic expansion approach that incorporates concept similarity is introduced and a generalized fuzzy set retrieval model that applies expansion during query evaluation is presented. While not commonly used in present information retrieval systems, it appears that the fuzzy set model comprises the flexibility needed when generalizing to an ontology-based retrieval model and, with the introduction of a hierarchical fuzzy aggregation principle, compound concepts can be handled in a straightforward and natural manner.

Content

A dissertation Presented to the Faculties of Roskilde University in Partial Fulfillment of the Requirement for the Degree of Doctor of Philosophy. Vgl. unter: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.987 oder http://coitweb.uncc.edu/~ras/RS/Onto-Retrieval.pdf.

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Abstract

The results of this thesis are intended to support the information architect in designing a solution for improved search in a corporate environment. Specifically we have examined the type of search problems that require a domain model to enhance the search process. There are several approaches to modeling a domain. We have considered 3 different types of domain modeling schemes; taxonomy, thesaurus and ontology. The intention is to support the information architect in making an informed choice between one or more of these schemes. In our opinion the main criteria for this choice are the modeling characteristics of a scheme and the suitability for application in the search process. The second chapter is a discussion of modeling characteristics of each scheme, followed by a comparison between them. This should give an information architect an idea of which aspects of a domain can be modeled with each scheme. What is missing here is an indication of the effort required to model a domain with each scheme. There are too many factors that influence the amount of required effort, ranging from measurable factors like domain size and resource characteristics to cultural matters such as the willingness to share knowledge and the existence of a project champion in the team to keep the project running. The third chapter shows what role domain models can play in each part of the search process. This gives an idea of the problems that domain models can solve. We have split the search process into individual parts to show that domain models can be applied very differently in the process. The fourth chapter makes recommendations about the suitability of each individualdomain modeling scheme for improving search. Each scheme has particular characteristics that make it especially suitable for a domain or a search problem. In the appendix each case study is described in detail. These descriptions are intended to serve as a benchmark. The current problem of the enterprise can be compared to those described to see which case study is most similar, which solution was chosen, which problems arose and how they were dealt with. An important issue that we have not touched upon in this thesis is that of maintenance. The real problems of a domain model are revealed when it is applied in a search system and its deficits and wrong assumptions become clear. Adaptation and maintenance are always required. Unfortunately we have not been able to glean sufficient information about maintenance issues from our case studies to draw any meaningful conclusions.

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Abstract

In the Internet information space, advanced information retrieval (IR) methods and automatic text processing are used in conjunction with traditional knowledge organization systems (KOS). New information technology provides a platform for better KOS publishing, exploitation and sharing both for human and machine use. Networked KOS services are now being planned and developed as powerful tools for resource discovery. They will enable automatic contextualisation, interpretation and query matching to different indexing languages. The Semantic Web promises to be an environment in which the quality of semantic relationships in bibliographic classification systems can be fully exploited. Their use in the networked environment is, however, limited by the fact that they are not prepared or made available for advanced machine processing. The UDC was chosen for this research because of its widespread use and its long-term presence in online information retrieval systems. It was also the first system to be used for the automatic classification of Internet resources, and the first to be made available as a classification tool on the Web. The objective of this research is to establish the advantages of using UDC for information retrieval in a networked environment, to highlight the problems of automation and classification exchange, and to offer possible solutions. The first research question was is there enough evidence of the use of classification on the Internet to justify further development with this particular environment in mind? The second question is what are the automation requirements for the full exploitation of UDC and its exchange? The third question is which areas are in need of improvement and what specific recommendations can be made for implementing the UDC in a networked environment? A summary of changes required in the management and development of the UDC to facilitate its full adaptation for future use is drawn from this analysis.

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Abstract

This research explores, using a Grounded Theory approach, the question of how a particular group of undergraduate university students differentiates the values of retrieved information in a contemporary research process. Specifically it attempts to isolate and label those specific techniques, processes, formulae-both objective and subjective-that the students use to identify, prioritize, and successfully incorporate the most useful and valuable information into their research project. The research reviews the relevant literature covering the areas of: epistemology, knowledge acquisition, and cognitive learning theory; early relevance research; the movement from relevance models to information seeking in context; and the proximate recent research. A research methodology is articulated using a Grounded Theory approach, and the research process and research participants are fully explained and described. The findings of the research are set forth using three Thematic Sets- Traditional Relevance Measures; Structural Frames; and Metaphors: General and Ecological-using the actual discourse of the study participants, and a theoretical construct is advanced. Based on that construct, it can be theorized that identification and analysis of the metaphorical language that the particular students in this study used, both by way of general and ecological metaphors-their stories-about how they found, handled, and evaluated information, can be a very useful tool in understanding how the students identified, prioritized, and successfully incorporated the most useful and relevant information into their research projects. It also is argued that this type of metaphorical analysis could be useful in providing a bridging mechanism for a broader understanding of the relationships between traditional user relevance studies and the concepts of frame theory and sense-making. Finally, a corollary to Whitmire's original epistemological hypothesis is posited: Students who were more adept at using metaphors-either general or ecological-appeared more comfortable with handling contradictory information sources, and better able to articulate their valuing decisions. The research concludes with a discussion of the implications for both future research in the Library and Information Science field, and for the practice of both Library professionals and classroom instructors involved in assisting students involved in information valuing decision-making in a research process.

Content

Dissertation Presented to the Faculty of the Graduate School of The University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. Vgl. unter: http://dspace.lib.utexas.edu/bitstream/2152/701/1/strongr80063.pdf.

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Abstract

The focus of this thesis is information use. Although a key concept in information behaviour, information use has received little attention from information science researchers. Studies of other key concepts such as information need and information seeking are dominant in information behaviour research. Information use is an area of interest to information professionals who rely on research outcomes to shape their practice. There are few empirical studies of how people actually use information that might guide and refine the development of information systems, products and services.

Content

A thesis submitted to the University of Technology, Sydney in fulfilment of the requirements for the degree of Doctor of Philosophy. - Vgl. unter: http://epress.lib.uts.edu.au/dspace/bitstream/2100/309/2/02whole.pdf.

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Abstract

While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols. Therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...

Content

Inhalt: INFORMATION LANGUAGES: A LINGUISTIC APPROACH MULTILINGUAL ASPECTS IN INFORMATION STORAGE AND RETRIEVAL COMPATIBILITY AND CONVERTIBILITY OF INFORMATION LANGUAGES CURRENT TRENDS IN MULTILINGUAL ACCESS BUILDING UDC-BASED MULTILINGUAL THESAURI ONLINE APPLICATIONS OF THE UDC-BASED MULTILINGUAL THESAURI THE IMPACT OF SPECIFICITY ON THE RETRIEVAL POWER OF A UDC-BASED MULTILINGUAL THESAURUS FINAL REMARKS AND GENERAL CONCLUSIONS Proefschrift voorgelegd tot het behalen van de graad van doctor in de Taal- en Letterkunde aan de Universiteit Antwerpen. - Vgl.: http://dlist.sir.arizona.edu/1862/.

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Abstract

As the Web continues to grow and encompass broader and more diverse sources of information, providing effective search facilities to users becomes an increasingly challenging problem. To help users deal with the deluge of Web-accessible information, we propose a search system which makes use of context to improve search results in a scalable way. By context, we mean any sources of information, in addition to any search query, that provide clues about the user's true information need. For instance, a user's bookmarks and search history can be considered a part of the search context. We consider two types of context-based search. The first type of functionality we consider is "similarity search." In this case, as the user is browsing Web pages, URLs for pages similar to the current page are retrieved and displayed in a side panel. No query is explicitly issued; context alone (i.e., the page currently being viewed) is used to provide the user with useful related information. The second type of functionality involves taking search context into account when ranking results to standard search queries. Web search differs from traditional information retrieval tasks in several major ways, making effective context-sensitive Web search challenging. First, scalability is of critical importance. With billions of publicly accessible documents, the Web is much larger than traditional datasets. Similarly, with millions of search queries issued each day, the query load is much higher than for traditional information retrieval systems. Second, there are no guarantees on the quality ofWeb pages, with Web-authors taking an adversarial, rather than cooperative, approach in attempts to inflate the rankings of their pages. Third, there is a significant amount of metadata embodied in the link structure corresponding to the hyperlinks between Web pages that can be exploitedduring the retrieval process. In this thesis, we design a search system, using the Stanford WebBase platform, that exploits the link structure of the Web to provide scalable, context-sensitive search.

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Abstract

This dissertation studies ontology mapping: the problem of finding semantic correspondences between similar elements of different ontologies. In the dissertation, elements denote classes or properties of ontologies. The goal of this research is to use ontology mapping to make heterogeneous information more accessible. The World Wide Web (WWW) now is widely used as a universal medium for information exchange. Semantic interoperability among different information systems in the WWW is limited due to information heterogeneity, and the non semantic nature of HTML and URLs. Ontologies have been suggested as a way to solve the problem of information heterogeneity by providing formal, explicit definitions of data and reasoning ability over related concepts. Given that no universal ontology exists for the WWW, work has focused on finding semantic correspondences between similar elements of different ontologies, i.e., ontology mapping. Ontology mapping can be done either by hand or using automated tools. Manual mapping becomes impractical as the size and complexity of ontologies increases. Full or semi-automated mapping approaches have been examined by several research studies. Previous full or semiautomated mapping approaches include analyzing linguistic information of elements in ontologies, treating ontologies as structural graphs, applying heuristic rules and machine learning techniques, and using probabilistic and reasoning methods etc. In this paper, two generic ontology mapping approaches are proposed. One is the PRIOR+ approach, which utilizes both information retrieval and artificial intelligence techniques in the context of ontology mapping. The other is the non-instance learning based approach, which experimentally explores machine learning algorithms to solve ontology mapping problem without requesting any instance. The results of the PRIOR+ on different tests at OAEI ontology matching campaign 2007 are encouraging. The non-instance learning based approach has shown potential for solving ontology mapping problem on OAEI benchmark tests.

Content

Submitted to the Graduate Faculty of School of Information Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy.

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Abstract

Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work. This thesis contains a detailed analysis of three specialized systems for the interactive exploration of large graphs, relating the intended tasks to the spatial layout and visual encoding choices. We present two novel algorithms for specialized layout and drawing that use quite different visual metaphors. The H3 system for visualizing the hyperlink structures of web sites scales to datasets of over 100,000 nodes by using a carefully chosen spanning tree as the layout backbone, 3D hyperbolic geometry for a Focus+Context view, and provides a fluid interactive experience through guaranteed frame rate drawing. The Constellation system features a highly specialized 2D layout intended to spatially encode domain-specific information for computational linguists checking the plausibility of a large semantic network created from dictionaries. The Planet Multicast system for displaying the tunnel topology of the Internet's multicast backbone provides a literal 3D geographic layout of arcs on a globe to help MBone maintainers find misconfigured long-distance tunnels. Each of these three systems provides a very different view of the graph structure, and we evaluate their efficacy for the intended task. We generalize these findings in our analysis of the importance of interactivity and specialization for graph visualization systems that are effective and scalable.

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Abstract

An information system like the Web is a continuously evolving system consisting of multiple heterogeneous information sources, covering a wide domain of discourse, and a huge number of users (human or software) with diverse characteristics and needs, that produce and consume information. The challenge nowadays is to build a scalable information infrastructure enabling the effective, accurate, content based retrieval of information, in a way that adapts to the characteristics and interests of the users. The aim of this work is to propose formally sound methods for building such an information network based on ontologies which are widely used and are easy to grasp by ordinary Web users. The main results of this work are: - A novel scheme for indexing and retrieving objects according to multiple aspects or facets. The proposed scheme is a faceted scheme enriched with a method for specifying the combinations of terms that are valid. We give a model-theoretic interpretation to this model and we provide mechanisms for inferring the valid combinations of terms. This inference service can be exploited for preventing errors during the indexing process, which is very important especially in the case where the indexing is done collaboratively by many users, and for deriving "complete" navigation trees suitable for browsing through the Web. The proposed scheme has several advantages over the hierarchical classification schemes currently employed by Web catalogs, namely, conceptual clarity (it is easier to understand), compactness (it takes less space), and scalability (the update operations can be formulated more easily and be performed more effciently). - A exible and effecient model for building mediators over ontology based information sources. The proposed mediators support several modes of query translation and evaluation which can accommodate various application needs and levels of answer quality. The proposed model can be used for providing users with customized views of Web catalogs. It can also complement the techniques for building mediators over relational sources so as to support approximate translation of partially ordered domain values.