Search (3 results, page 1 of 1)

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Abstract

In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.

Source

Information Systems. 37(2012) no. 4, S.294-305

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Abstract

Die auf Basis vernetzter Computer realisierbare Möglichkeit einer universalen Enzyklopädie führt aufgrund der dabei technisch notwendigen Reduktion auf nur eine Sorte Repräsentanten zu Systemen, bei denen entweder nur Gegenstände repräsentiert werden, die auch Begriffe vertreten, oder nur Begriffe, die auch Gegenstände vertreten. In der Dissertation werden als Beispiele solcher Repräsentationssysteme die logischen Systeme von Gottlob Frege und Johann Heinrich Lambert untersucht. Freges System, basierend auf der Annahme der Objektivität von Bedeutungen, war durch die Nachweisbarkeit einer Antinomie gescheitert, weshalb von Philosophen im 20. Jahrhundert die Existenz einer objektiven Bedeutung von Ausdrücken und die Übersetzbarkeit der Gedanken aus den natürlichen Sprachen in eine formale Sprache in Frage gestellt wurde. In der Dissertation wird nachgewiesen, daß diese Konsequenz voreilig war und daß die Antinomie auch bei Annahme der Objektivität von Wissen erst durch zwei Zusatzforderungen in Freges Logik ausgelöst wird: die eineindeutige Zuordnung eines Gegenstands zu jedem Begriff sowie die scharfen Begrenzung der Begriffe, die zur Abgeschlossenheit des Systems zwingt. Als Alternative wird das Begriffssystem Lamberts diskutiert, bei dem jeder Gegenstand durch einen Begriff und gleichwertig durch Gesamtheiten von Begriffen vertreten wird und Begriffe durch Gesamtheiten von Begriffen ersetzbar sind. Beide die Antinomie auslösenden Bedingungen sind hier nicht vorhanden, zugleich ist die fortschreitende Entwicklung von Wissen repräsentierbar. Durch die mengentheoretische Rekonstruktion des Begriffssystems Lamberts in der Dissertation wird dessen praktische Nutzbarkeit gezeigt. Resultat der Dissertation ist der Nachweis, daß es Repräsentationssysteme gibt, die nicht auf die für die Prüfung der Verbindlichkeit der Einträge in die Enzyklopädie notwendige Annahme der Verobjektivierbarkeit von Wissen verzichten müssen, weil ihnen nicht jene die Antinomie auslösenden Voraussetzungen zugrunde liegen.

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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.