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Content

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

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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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Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

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Abstract

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

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Abstract

Wikis sind ein geeignetes Mittel zur Umsetzung von umfangreichen Wissenssammlungen wie Lexika oder Enzyklopädien. Bestes Beispiel dafür bildet die weltweit erfolgreiche freie On-line-Enzyklopadie Wikipedia. Jedoch ist es mit konventionellen Wiki-Umgebungen nicht moglich das Potential der gespeicherten Texte vollends auszuschopfen. Eine neue Möglichkeit bieten semantische Wikis, deren Inhalte mithilfe von maschinenlesbaren Annotationen semantische Bezüge erhalten. Die hier vorliegende Bachelorarbeit greift dies auf und überführt Teile des "Reallexikons zur deutschen Kunstgeschichte" in ein semantisches Wiki. Aufgrund einer Semantic MediaWiki-Installation soll uberpruft werden, inwieweit die neue Technik fur die Erschließung des Lexikons genutzt werden kann. Mit einem Beispiel-Wiki für das RdK auf beigefügter CD.

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Abstract

Knowledge explosion in various fields during recent years has resulted in the creation of vast amounts of on-line scientific literature. Food Science &Technology (FST) is also an important subject domain where rapid developments are taking place due to diverse research and development activities. As a result, information storage and retrieval has become very complex and current information retrieval systems (IRs) are being challenged in terms of both adequate precision and response time. To overcome these limitations as well as to provide naturallanguage based effective retrieval, a suitable knowledge engineering framework needs to be applied to represent, share and discover information. Semantic web technologies provide mechanisms for creating knowledge bases, ontologies and rules for handling data that promise to improve the quality of information retrieval. Ontologies are the backbone of such knowledge systems. This paper presents a framework for semantic representation of a large repository of content in the domain of FST.

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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

More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.

Date

26.12.2011 13:40:22

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Abstract

Literature-based discovery (LBD) research aims at finding effective computational methods for predicting previously unknown connections between clusters of research papers from disparate research areas. Existing methods encompass two general approaches. The first approach searches for these unknown connections by examining the textual contents of research papers. In addition to the existing textual features, the second approach incorporates structural features of scientific literatures, such as citation structures. These approaches, however, have not considered research papers' latent bibliographic metadata structures as important features that can be used for predicting previously unknown relationships between them. This thesis investigates a new graph-based LBD method that exploits the latent bibliographic metadata connections between pairs of research papers. The heterogeneous bibliographic information network is proposed as an efficient graph-based data structure for modeling the complex relationships between these metadata. In contrast to previous approaches, this method seamlessly combines textual and citation information in the form of pathbased metadata features for predicting future co-citation links between research papers from disparate research fields. The results reported in this thesis provide evidence that the method is effective for reconstructing the historical literature-based discovery hypotheses. This thesis also investigates the effects of semantic modeling and topic modeling on the performance of the proposed method. For semantic modeling, a general-purpose word sense disambiguation technique is proposed to reduce the lexical ambiguity in the title and abstract of research papers. The experimental results suggest that the reduced lexical ambiguity did not necessarily lead to a better performance of the method. This thesis discusses some of the possible contributing factors to these results. Finally, topic modeling is used for learning the latent topical relations between research papers. The learned topic model is incorporated into the heterogeneous bibliographic information network graph and allows new predictive features to be learned. The results in this thesis suggest that topic modeling improves the performance of the proposed method by increasing the overall accuracy for predicting the future co-citation links between disparate research papers.

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Abstract

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

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Date

20. 1.2015 18:30:22

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Abstract

Innerhalb der Gedächtnisinstitutionen Bibliothek, Museum und Archiv gibt es je eigene Beschreibungsmodelle der beherbergten Objekte und Materialien. Für eine genauere bibliografische Erschließung wurde im Bibliotheksbereich das von Benutzerbedürfnissen ausgehende, statische Modell "Functional Requirements for Bibliographic Records" (FRBR) geschaffen, dessen ungenauer »Werk«-Begriff ebenso thematisiert wird wie die schwer zu realisierende Übertragbarkeit des Modells auf Nicht-Buchmaterialien. Die Museumswelt orientiert die Darstellung ihrer Bestände am CIDOC Conceptual Reference Model (CRM), das sich hinsichtlich der Beschreibung heterogener Museumsobjekte, also Artefakten künstlerischer und intellektueller Gestaltung, als hilfreich erwiesen hat. In gegenseitigem Austausch zwischen IFLA und ICOM wurde FRBR mit CRM harmonisiert. Das Ergebnis, FRBRoo (objektorientiertes FRBR), zeigt seine Vorzüge zum einen in einer strengeren Interpretation der Entitäten der Gruppe 1 des FRBR-Modells und zum anderen in einer genaueren Abbildung von Prozessen bzw. Ereignissen. Beispiele zum Anwendungsbezug von FRBRoo zeigen dessen Zugewinn für die wissenschaftliche Erschließung hand-, druck- und online-schriftlicher Quellen, Werken der Darstellenden Kunst, Landkarten und Musikalien innerhalb einer CRM-basierten Datenbank.

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Abstract

This article comprises a literature review and conceptual analysis of Topic Maps-the ISO standard for representing information about the structure of information resources-according to the principles of Knowledge Organization (KO). Using the main principles from this discipline, the study shows how Topic Maps is proposed as an ontology model independent of technology. Topic Maps constitutes a 'bibliographic' meta-language able to represent, extend, and integrate almost all existing Knowledge Organization Systems (KOS) in a standards-based generic model applicable to digital content and to the Web. This report also presents an inventory of the current applications of Topic Maps in Libraries, Archives, and Museums (LAM), as well as in the Digital Humanities. Finally, some directions for further research are suggested, which relate Topic Maps to the main research trends in KO.

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Abstract

The number of publications in mathematics increases faster each year. Presently far more than 100,000 mathematically relevant journal articles and books are published annually. Efficient and high-quality content analysis of this material is important for mathematical bibliographic services such as ZBMath or MathSciNet. Content analysis has different facets and levels: classification, keywords, abstracts and reviews, and (in the future) formula analysis. It is the opinion of the authors that the different levels have to be enhanced and combined using the methods and technology of the Semantic Web. In the presentation, the problems and deficits of the existing methods and tools, the state of the art and current activities are discussed. As a first step, the Mathematical Subject Classification Scheme (MSC), has been encoded with Simple Knowledge Organization System (SKOS) and Resource Description Framework (RDF) at its recent revision to MSC2010. The use of SKOS principally opens new possibilities for the enrichment and wider deployment of this classification scheme and for machine-based content analysis of mathematical publications.

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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

How information resources can be meaningfully related has been addressed in contexts from bibliographic entries to hyperlinks and, more recently, linked data. The genre structure and relationships among genre structure constituents shed new light on organizing information by purpose or function. This study examines the relationships among a set of functional units previously constructed in a taxonomy, each of which is a chunk of information embedded in a document and is distinct in terms of its communicative function. Through a card-sort study, relationships among functional units were identified with regard to their occurrence and function. The findings suggest that a group of functional units can be identified, collocated, and navigated by particular relationships. Understanding how functional units are related to each other is significant in linking information pieces in documents to support finding, aggregating, and navigating information in a distributed information environment.

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Series

IFLA series on bibliographic control; vol. 42

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Content

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

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Abstract

Facet analysis is proposed as a general theory of knowledge organization, with an associated methodology that may be applied to the development of terminology tools in a variety of contexts and formats. Faceted classifications originated as a means of representing complexity in semantic content that facilitates logical organization and effective retrieval in a physical environment. This is achieved through meticulous analysis of concepts, their structural and functional status (based on fundamental categories), and their inter-relationships. These features provide an excellent basis for the general conceptual modelling of domains, and for the generation of KOS other than systematic classifications. This is demonstrated by the adoption of a faceted approach to many web search and visualization tools, and by the emergence of a facet based methodology for the construction of thesauri. Current work on the Bliss Bibliographic Classification (Second Edition) is investigating the ways in which the full complexity of faceted structures may be represented through encoded data, capable of generating intellectually and mechanically compatible forms of indexing tools from a single source. It is suggested that a number of research questions relating to the Semantic Web could be tackled through the medium of facet analysis.

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Abstract

A major stumbling block preventing machines from understanding text is the problem of entity disambiguation. While humans find it easy to determine that a person named in one story is the same person referenced in a second story, machines rely heavily on crude heuristics such as string matching and stemming to make guesses as to whether nouns are coreferent. A key advantage that humans have over machines is the ability to mentally make connections between ideas and, based on these connections, reason how likely two entities are to be the same. Mirroring this natural thought process, we have created a prototype framework for disambiguating entities that is based on connectedness. In this article, we demonstrate it in the practical application of disambiguating authors across a large set of bibliographic records. By representing knowledge from the records as edges in a graph between a subject and an object, we believe that the problem of disambiguating entities reduces to the problem of discovering the most strongly connected nodes in a graph. The knowledge from the records comes in many different forms, such as names of people, date of publication, and themes extracted from the text of the abstract. These different types of knowledge are fused to create the graph required for disambiguation. Furthermore, the resulting graph and framework can be used for more complex operations.