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  • × theme_ss:"Wissensrepräsentation"
  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.19 
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.09 
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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.
  3. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.07 
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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.
  4. Pepper, S.; Arnaud, P.J.L.: Absolutely PHAB : toward a general model of associative relations (2020) 0.05 
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    Abstract
    There have been many attempts at classifying the semantic modification relations (R) of N + N compounds but this work has not led to the acceptance of a definitive scheme, so that devising a reusable classification is a worthwhile aim. The scope of this undertaking is extended to other binominal lexemes, i.e. units that contain two thing-morphemes without explicitly stating R, like prepositional units, N + relational adjective units, etc. The 25-relation taxonomy of Bourque (2014) was tested against over 15,000 binominal lexemes from 106 languages and extended to a 29-relation scheme ("Bourque2") through the introduction of two new reversible relations. Bourque2 is then mapped onto Hatcher's (1960) four-relation scheme (extended by the addition of a fifth relation, similarity , as "Hatcher2"). This results in a two-tier system usable at different degrees of granularities. On account of its semantic proximity to compounding, metonymy is then taken into account, following Janda's (2011) suggestion that it plays a role in word formation; Peirsman and Geeraerts' (2006) inventory of 23 metonymic patterns is mapped onto Bourque2, confirming the identity of metonymic and binominal modification relations. Finally, Blank's (2003) and Koch's (2001) work on lexical semantics justifies the addition to the scheme of a third, superordinate level which comprises the three Aristotelean principles of similarity, contiguity and contrast.
  5. Handbook on ontologies (2004) 0.05 
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    RSWK
    Informationssystem / Wissenstechnik / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Semantic Web / Wissensbasiertes System / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Informationssystem / Konzeptionelle Modellierung / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Subject
    Informationssystem / Wissenstechnik / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Semantic Web / Wissensbasiertes System / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Informationssystem / Konzeptionelle Modellierung / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
  6. Priss, U.: Faceted knowledge representation (1999) 0.04 
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    Abstract
    Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
    Date
    22. 1.2016 17:30:31
  7. Li, J.; Zhang, Z.; Li, X.; Chen, H.: Kernel-based learning for biomedical relation extraction (2008) 0.04 
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    Abstract
    Relation extraction is the process of scanning text for relationships between named entities. Recently, significant studies have focused on automatically extracting relations from biomedical corpora. Most existing biomedical relation extractors require manual creation of biomedical lexicons or parsing templates based on domain knowledge. In this study, we propose to use kernel-based learning methods to automatically extract biomedical relations from literature text. We develop a framework of kernel-based learning for biomedical relation extraction. In particular, we modified the standard tree kernel function by incorporating a trace kernel to capture richer contextual information. In our experiments on a biomedical corpus, we compare different kernel functions for biomedical relation detection and classification. The experimental results show that a tree kernel outperforms word and sequence kernels for relation detection, our trace-tree kernel outperforms the standard tree kernel, and a composite kernel outperforms individual kernels for relation extraction.
  8. Semantische Technologien : Grundlagen - Konzepte - Anwendungen (2012) 0.03 
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    RSWK
    Wissensrepräsentation / Semantisches Netz / RDF <Informatik> / OWL <Informatik> / Aufsatzsammlung
    Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung
    Semantic Web / Web Services / Semantische Modellierung / Ontologie <Wissensverarbeitung> / Suche / Navigieren / Anwendungsbereich / Aufsatzsammlung
    Subject
    Wissensrepräsentation / Semantisches Netz / RDF <Informatik> / OWL <Informatik> / Aufsatzsammlung
    Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung
    Semantic Web / Web Services / Semantische Modellierung / Ontologie <Wissensverarbeitung> / Suche / Navigieren / Anwendungsbereich / Aufsatzsammlung
  9. Zhang, M.; Zhou, G.D.; Aw, A.: Exploring syntactic structured features over parse trees for relation extraction using kernel methods (2008) 0.03 
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    Abstract
    Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This paper proposes to use the convolution kernel over parse trees together with support vector machines to model syntactic structured information for relation extraction. Compared with linear kernels, tree kernels can effectively explore implicitly huge syntactic structured features embedded in a parse tree. Our study reveals that the syntactic structured features embedded in a parse tree are very effective in relation extraction and can be well captured by the convolution tree kernel. Evaluation on the ACE benchmark corpora shows that using the convolution tree kernel only can achieve comparable performance with previous best-reported feature-based methods. It also shows that our method significantly outperforms previous two dependency tree kernels for relation extraction. Moreover, this paper proposes a composite kernel for relation extraction by combining the convolution tree kernel with a simple linear kernel. Our study reveals that the composite kernel can effectively capture both flat and structured features without extensive feature engineering, and easily scale to include more features. Evaluation on the ACE benchmark corpora shows that the composite kernel outperforms previous best-reported methods in relation extraction.
  10. Nguyen, P.H.P.; Kaneiwa, K.; Nguyen, M.-Q.: Ontology inferencing rules and operations in conceptual structure theory (2010) 0.03 
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    Abstract
    This paper describes in detail the inferencing rules and operations concerning an ontology formalism previously proposed under Conceptual Structure Theory. The ontology consists of hierarchies of concept, relation and meta-relation types, and formal relationships between them, in particular between arguments of relation and meta-relation types. Inferencing rules are described as well as operations to maintain the ontology in a semantically consistent state at all times. The main aim of the paper is to provide a blue print for the implementation of ontologies in the future Semantic Web.
  11. Ejei, F.; Beheshti, M.S.H.; Rajabi, T.; Ejehi, Z.: Enriching semantic relations of basic sciences ontology (2017) 0.03 
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    Abstract
    Ontology is the tool for representing knowledge in the fields of knowledge organization and artificial intelligence, and in the past decade, has gained attention in the semantic web as well. The main necessity in developing an ontology is generating a hierarchical structure of the concepts and the next requirement is creating and determining the type of the semantic relations among concepts. The present article introduces a semi-automated method for enriching semantic relations in the basic sciences ontology, which was developed based on domain-specific thesauri. In the proposed method, first the hierarchical relations in the ontology are reviewed and refined in order to distinguish their different types. In the next step, the concepts in the ontology are classified and the semantic relations among the concepts, based on the associative relationships in the thesaurus and semantic relation patterns extracted from a top-level ontology, are distinguished and added to the ontology. Using this method, semantic relations in the area of chemistry in the basic sciences ontology were refined and enriched. Almost seventy percent of the associative relationships were directly converted to semantic relations in the ontology. The remaining thirty percent are the inter-concept relations that can be concluded from other relations if the other associative relationships are correctly converted to semantic relations.
    Date
    29. 9.2017 18:39:48
  12. Soergel, D.: Towards a relation ontology for the Semantic Web (2011) 0.02 
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    Abstract
    The Semantic Web consists of data structured for use by computer programs, such as data sets made available under the Linked Open Data initiative. Much of this data is structured following the entity-relationship model encoded in RDF for syntactic interoperability. For semantic interoperability, the semantics of the relationships used in any given dataset needs to be made explicit. Ultimately this requires an inventory of these relationships structured around a relation ontology. This talk will outline a blueprint for such an inventory, including a format for the description/definition of binary and n-ary relations, drawing on ideas put forth in the classification and thesaurus community over the last 60 years, upper level ontologies, systems like FrameNet, the Buffalo Relation Ontology, and an analysis of linked data sets.
  13. Blanco, E.; Moldovan, D.: ¬A model for composing semantic relations (2011) 0.02 
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    Abstract
    This paper presents a model to compose semantic relations. The model is independent of any particular set of relations and uses an extended definition for semantic relations. This extended definition includes restrictions on the domain and range of relations and utilizes semantic primitives to characterize them. Primitives capture elementary properties between the arguments of a relation. An algebra for composing semantic primitives is used to automatically identify the resulting relation of composing a pair of compatible relations. Inference axioms are obtained. Axioms take as input a pair of semantic relations and output a new, previously ignored relation. The usefulness of this proposed model is shown using PropBank relations. Eight inference axioms are obtained and their accuracy and productivity are evaluated. The model offers an unsupervised way of accurately extracting additional semantics from text.
  14. Schutz, A.; Buitelaar, P.: RelExt: a tool for relation extraction from text in ontology extension (2005) 0.02 
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    Abstract
    Domain ontologies very rarely model verbs as relations holding between concepts. However, the role of the verb as a central connecting element between concepts is undeniable. Verbs specify the interaction between the participants of some action or event by expressing relations between them. In parallel, it can be argued from an ontology engineering point of view that verbs express a relation between two classes that specify domain and range. The work described here is concerned with relation extraction for ontology extension along these lines. We describe a system (RelExt) that is capable of automatically identifying highly relevant triples (pairs of concepts connected by a relation) over concepts from an existing ontology. RelExt works by extracting relevant verbs and their grammatical arguments (i.e. terms) from a domain-specific text collection and computing corresponding relations through a combination of linguistic and statistical processing. The paper includes a detailed description of the system architecture and evaluation results on a constructed benchmark. RelExt has been developed in the context of the SmartWeb project, which aims at providing intelligent information services via mobile broadband devices on the FIFA World Cup that will be hosted in Germany in 2006. Such services include location based navigational information as well as question answering in the football domain.
  15. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.02 
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    Abstract
    Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.
    Date
    20. 1.2015 18:30:22
  16. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.02 
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    Abstract
    Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
    Date
    20. 1.2015 18:30:22
  17. Semantic digital libraries (2009) 0.02 
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    RSWK
    Elektronische Bibliothek / Semantic Web / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Subject
    Elektronische Bibliothek / Semantic Web / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
  18. Semantic knowledge and semantic representations (1995) 0.02 
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    RSWK
    Semantik / Sprachstörung / Aufsatzsammlung (BVB)
    Subject
    Semantik / Sprachstörung / Aufsatzsammlung (BVB)
  19. Amirhosseini, M.: Theoretical base of quantitative evaluation of unity in a thesaurus term network based on Kant's epistemology (2010) 0.02 
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    Abstract
    The quantitative evaluation of thesauri has been carried out much further since 1976. This type of evaluation is based on counting of special factors in thesaurus structure, some of which are counting preferred terms, non preferred terms, cross reference terms and so on. Therefore, various statistical tests have been proposed and applied for evaluation of thesauri. In this article, we try to explain some ratios in the field of unity quantitative evaluation in a thesaurus term network. Theoretical base of the ratios' indicators and indices construction, and epistemological thought in this type of quantitative evaluation, are discussed in this article. The theoretical base of quantitative evaluation is the epistemological thought of Immanuel Kant's Critique of pure reason. The cognition states of transcendental understanding are divided into three steps, the first is perception, the second combination and the third, relation making. Terms relation domains and conceptual relation domains can be analyzed with ratios. The use of quantitative evaluations in current research in the field of thesaurus construction prepares a basis for a restoration period. In modern thesaurus construction, traditional term relations are analyzed in detail in the form of new conceptual relations. Hence, the new domains of hierarchical and associative relations are constructed in the form of relations between concepts. The newly formed conceptual domains can be a suitable basis for quantitative evaluation analysis in conceptual relations.
  20. Stock, W.: Begriffe und semantische Relationen in der Wissensrepräsentation (2009) 0.02 
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    Abstract
    Begriffsorientiertes Information Retrieval bedarf einer informationswissenschaftlichen Theorie der Begriffe sowie der semantischen Relationen. Ein Begriff wird durch seine Intension und Extension sowie durch Definitionen bestimmt. Dem Problem der Vagheit begegnen wir durch die Einführung von Prototypen. Wichtige Definitionsarten sind die Begriffserklärung (nach Aristoteles) und die Definition über Familienähnlichkeiten (im Sinne Wittgensteins). Wir modellieren Begriffe als Frames (in der Version von Barsalou). Die zentrale paradigmatische Relation in Wissensordnungen ist die Hierarchie, die in verschiedene Arten zu gliedern ist: Hyponymie zerfällt in die Taxonomie und die einfache Hyponymie, Meronymie in eine ganze Reihe unterschiedlicher Teil-Ganzes-Beziehungen. Wichtig für praktische Anwendungen ist die Transitivität der jeweiligen Relation. Eine unspezifische Assoziationsrelation ist bei den angepeilten Anwendungen wenig hilfreich und wird durch ein Bündel von generalisierbaren und fachspezifischen Relationen ersetzt. Unser Ansatz fundiert neue Optionen der Anwendung von Wissensordnungen in der Informationspraxis neben ihrem "klassischen" Einsatz beim Information Retrieval: Erweiterung von Suchanfragen (Anwendung der semantischen Nähe), automatisches Schlussfolgern (Anwendung der terminologischen Logik in Vorbereitung eines semantischen Web) und automatische Berechnungen (bei Funktionalbegriffen mit numerischen Wertangaben).

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