Search (17 results, page 1 of 1)

  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"a"
  • × type_ss:"el"
  1. Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013) 0.01
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    Abstract
    Dieser Artikel adressiert einen Randbereich des Wissensmanagements: die Schnittstelle zwischen Unternehmens-externen Informationen im Internet und den Leistungsprozessen eines Unternehmens. Diese Schnittstelle ist besonders für Unternehmen von Interesse, deren Leistungsprozesse von externen Informationen abhängen und die auf diese Prozesse angewiesen sind. Wir zeigen an zwei Fallbeispielen, dass die inhaltliche Filterung von Informationen beim Eintritt ins Unternehmen ein wichtiges Werkzeug darstellt, um daran anschließende Wissens- und Informationsmanagementprozesse effizient zu gestalten.
    Date
    29. 9.2015 18:56:44
  2. Xu, G.; Cao, Y.; Ren, Y.; Li, X.; Feng, Z.: Network security situation awareness based on semantic ontology and user-defined rules for Internet of Things (2017) 0.00
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    Abstract
    Internet of Things (IoT) brings the third development wave of the global information industry which makes users, network and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response and predicting the development trend of IoT security, a new paradigm called network security situation awareness (NSSA) is proposed. However, it is limited by its ability to mine and evaluate security situation elements from multi-source heterogeneous network security information. To solve this problem, this paper proposes an IoT network security situation awareness model using situation reasoning method based on semantic ontology and user-defined rules. Ontology technology can provide a unified and formalized description to solve the problem of semantic heterogeneity in the IoT security domain. In this paper, four key sub-domains are proposed to reflect an IoT security situation: context, attack, vulnerability and network flow. Further, user-defined rules can compensate for the limited description ability of ontology, and hence can enhance the reasoning ability of our proposed ontology model. The examples in real IoT scenarios show that the ability of the network security situation awareness that adopts our situation reasoning method is more comprehensive and more powerful reasoning abilities than the traditional NSSA methods. [http://ieeexplore.ieee.org/abstract/document/7999187/]
  3. Wang, Y.-H.; Jhuo, P.-S.: ¬A semantic faceted search with rule-based inference (2009) 0.00
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    Abstract
    Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.
  4. Griffiths, T.L.; Steyvers, M.: ¬A probabilistic approach to semantic representation (2002) 0.00
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    Date
    29. 6.2015 14:55:01
    29. 6.2015 16:09:05
  5. Gómez-Pérez, A.; Corcho, O.: Ontology languages for the Semantic Web (2015) 0.00
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    Abstract
    Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.
  6. Putkey, T.: Using SKOS to express faceted classification on the Semantic Web (2011) 0.00
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    Abstract
    This paper looks at Simple Knowledge Organization System (SKOS) to investigate how a faceted classification can be expressed in RDF and shared on the Semantic Web. Statement of the Problem Faceted classification outlines facets as well as subfacets and facet values. Hierarchical relationships and associative relationships are established in a faceted classification. RDF is used to describe how a specific URI has a relationship to a facet value. Not only does RDF decompose "information into pieces," but by incorporating facet values RDF also given the URI the hierarchical and associative relationships expressed in the faceted classification. Combining faceted classification and RDF creates more knowledge than if the two stood alone. An application understands the subjectpredicate-object relationship in RDF and can display hierarchical and associative relationships based on the object (facet) value. This paper continues to investigate if the above idea is indeed useful, used, and applicable. If so, how can a faceted classification be expressed in RDF? What would this expression look like? Literature Review This paper used the same articles as the paper A Survey of Faceted Classification: History, Uses, Drawbacks and the Semantic Web (Putkey, 2010). In that paper, appropriate resources were discovered by searching in various databases for "faceted classification" and "faceted search," either in the descriptor or title fields. Citations were also followed to find more articles as well as searching the Internet for the same terms. To retrieve the documents about RDF, searches combined "faceted classification" and "RDF, " looking for these words in either the descriptor or title.
  7. Hauff-Hartig, S.: Wissensrepräsentation durch RDF: Drei angewandte Forschungsbeispiele : Bitte recht vielfältig: Wie Wissensgraphen, Disco und FaBiO Struktur in Mangas und die Humanities bringen (2021) 0.00
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    Date
    22. 5.2021 12:43:05
  8. Rindflesch, T.C.; Aronson, A.R.: Semantic processing in information retrieval (1993) 0.00
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    Date
    29. 6.2015 14:51:28
  9. Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004) 0.00
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    Date
    29. 7.2011 14:44:56
  10. Priss, U.: Faceted knowledge representation (1999) 0.00
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    Date
    22. 1.2016 17:30:31
  11. Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004) 0.00
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    Date
    29. 7.2011 14:44:56
  12. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.00
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    Date
    3.12.2016 18:39:22
  13. Priss, U.: Description logic and faceted knowledge representation (1999) 0.00
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    Date
    22. 1.2016 17:30:31
  14. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.00
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    Date
    28.11.2016 12:43:22
  15. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.00
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    Date
    29. 7.2011 14:44:56
  16. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.00
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    Date
    16.11.2018 14:22:01
  17. Assem, M. van: Converting and integrating vocabularies for the Semantic Web (2010) 0.00
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    Date
    29. 7.2011 14:44:56