Search (13 results, page 1 of 1)

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Abstract

In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.

Content

A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.

Date

10. 1.2013 19:22:47

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Abstract

The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.

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

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

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

PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.

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Abstract

More and more information is available on-line every day. The greater the amount of on-line information, the greater the demand for tools that process and disseminate this information. Processing electronic information in the form of text and answering users' queries about that information intelligently is one of the great challenges in natural language processing and information retrieval. The research presented in this talk is centered on the latter of these two tasks: intelligent information retrieval. In order for information to be retrieved, it first needs to be formalized in a database or knowledge base. The ontology for this formalization and assumptions it is based on are crucial to successful intelligent information retrieval. We have concentrated our effort on developing an ontology for representing knowledge in the domains of experimental sciences, molecular biology in particular. We show that existing ontological models cannot be readily applied to represent this domain adequately. For example, the fundamental notion of ontology design that every "real" object is defined as an instance of a category seems incompatible with the universe where objects can change their category as a result of experimental procedures. Another important problem is representing complex structures such as DNA, mixtures, populations of molecules, etc., that are very common in molecular biology. We present extensions that need to be made to an ontology to cover these issues: the representation of transformations that change the structure and/or category of their participants, and the component relations and spatial structures of complex objects. We demonstrate examples of how the proposed representations can be used to improve the quality and completeness of answers to user queries; discuss techniques for evaluating ontologies and show a prototype of an Information Retrieval System that we developed.

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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

Industries have adopted a standardized set of practices for developing their products. In the automotive domain, the provision of safety-compliant systems is guided by ISO 26262, a standard that specifies a set of requirements and recommendations for developing automotive safety-critical systems. For being in compliance with ISO 26262, the safety lifecycle proposed by the standard must be included in the development process of a vehicle. Besides, a safety case that shows that the system is acceptably safe has to be provided. The provision of a safety case implies the execution of a precise documentation process. This process makes sure that the work products are available and traceable. Further, the documentation management is defined in the standard as a mandatory activity and guidelines are proposed/imposed for its elaboration. It would be appropriate to point out that a well-documented safety lifecycle will provide the necessary inputs for the generation of an ISO 26262-compliant safety case. The OSLC (Open Services for Lifecycle Collaboration) standard and the maturing stack of semantic web technologies represent a promising integration platform for enabling semantic interoperability between the tools involved in the safety lifecycle. Tools for requirements, architecture, development management, among others, are expected to interact and shared data with the help of domains specifications created in OSLC. This thesis proposes the creation of an OSLC tool-chain infrastructure for sharing safety-related information, where fragments of safety information can be generated. The steps carried out during the elaboration of this master thesis consist in the identification, representation, and shaping of the RDF resources needed for the creation of a safety case. The focus of the thesis is limited to a tiny portion of the ISO 26262 left-hand side of the V-model, more exactly part 6 clause 8 of the standard: Software unit design and implementation. Regardless of the use of a restricted portion of the standard during the execution of this thesis, the findings can be extended to other parts, and the conclusions can be generalize. This master thesis is considered one of the first steps towards the provision of an OSLC-based and ISO 26262-compliant methodological approach for representing and shaping the work products resulting from the execution of the safety lifecycle, documentation required in the conformation of an ISO-compliant safety case.

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Abstract

The dissertation establishes 'binominal lexeme' as a comparative concept and discusses its cross-linguistic typology and semantics. Informally, a binominal lexeme is a noun-noun compound or functional equivalent; more precisely, it is a lexical item that consists primarily of two thing-morphs between which there exists an unstated semantic relation. Examples of binominals include Mandarin Chinese ?? (tielù) [iron road], French chemin de fer [way of iron] and Russian ???????? ?????? (zeleznaja doroga) [iron:adjz road]. All of these combine a word denoting 'iron' and a word denoting 'road' or 'way' to denote the meaning railway. In each case, the unstated semantic relation is one of composition: a railway is conceptualized as a road that is composed (or made) of iron. However, three different morphosyntactic strategies are employed: compounding, prepositional phrase and relational adjective. This study explores the range of such strategies used by a worldwide sample of 106 languages to express a set of 100 meanings from various semantic domains, resulting in a classification consisting of nine different morphosyntactic types. The semantic relations found in the data are also explored and a classification called the Hatcher-Bourque system is developed that operates at two levels of granularity, together with a tool for classifying binominals, the Bourquifier. The classification is extended to other subfields of language, including metonymy and lexical semantics, and beyond language to the domain of knowledge representation, resulting in a proposal for a general model of associative relations called the PHAB model. The many findings of the research include universals concerning the recruitment of anchoring nominal modification strategies, a method for comparing non-binary typologies, the non-universality (despite its predominance) of compounding, and a scale of frequencies for semantic relations which may provide insights into the associative nature of human thought.

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Date

22. 6.2018 13:24:08
22. 6.2018 13:54:52

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Date

17. 3.2006 19:24:29

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Date

3. 2.2013 18:00:22

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Date

22. 7.2022 12:16:58

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Date

20. 1.2015 18:30:22