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  1. Pepper, S.: ¬The TAO of topic maps : finding the way in the age of infoglut (2002) 0.08 
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    Abstract
    Topic maps are a new ISO standard for describing knowledge structures and associating them with information resources. As such they constitute an enabling technology for knowledge management. Dubbed "the GPS of the information universe", topic maps are also destined to provide powerful new ways of navigating large and interconnected corpora. While it is possible to represent immensely complex structures using topic maps, the basic concepts of the model - Topics, Associations, and Occurrences (TAO) - are easily grasped. This paper provides a non-technical introduction to these and other concepts (the IFS and BUTS of topic maps), relating them to things that are familiar to all of us from the realms of publishing and information management, and attempting to convey some idea of the uses to which topic maps will be put in the future.
    Object
    Topic maps
  2. Siebers, Q.H.J.F.: Implementing inference rules in the Topic maps model (2006) 0.06 
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    Abstract
    This paper supplies a theoretical approach on implementing inference rules in the Topic Maps model. Topic Maps is an ISO standard that allows for the modeling and representation of knowledge in an interchangeable form, that can be extended by inference rules. These rules specify conditions for inferrable facts. Any implementation requires a syntax for storage in a file, a storage model and method for processing and a system to keep track of changes in the inferred facts. The most flexible and optimisable storage model is a controlled cache, giving options for processing. Keeping track of changes is done by listeners. One of the most powerful applications of inference rules in Topic Maps is interoperability. By mapping ontologies to each other using inference rules as converter, it is possible to exchange extendable knowledge. Any implementation must choose methods and options optimized for the system it runs on, with the facilities available. Further research is required to analyze optimization problems between options.
    Object
    Topic maps
  3. Cregan, A.: ¬An OWL DL construction for the ISO Topic Map Data Model (2005) 0.05 
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    Abstract
    Both Topic Maps and the W3C Semantic Web technologies are meta-level semantic maps describing relationships between information resources. Previous attempts at interoperability between XTM Topic Maps and RDF have proved problematic. The ISO's drafting of an explicit Topic Map Data Model [TMDM 05] combined with the advent of the W3C's XML and RDFbased Description Logic-equivalent Web Ontology Language [OWLDL 04] now provides the means for the construction of an unambiguous semantic model to represent Topic Maps, in a form that is equivalent to a Description Logic representation. This paper describes the construction of the proposed TMDM ISO Topic Map Standard in OWL DL (Description Logic equivalent) form. The construction is claimed to exactly match the features of the proposed TMDM. The intention is that the topic map constructs described herein, once officially published on the world-wide web, may be used by Topic Map authors to construct their Topic Maps in OWL DL. The advantage of OWL DL Topic Map construction over XTM, the existing XML-based DTD standard, is that OWL DL allows many constraints to be explicitly stated. OWL DL's suite of tools, although currently still somewhat immature, will provide the means for both querying and enforcing constraints. This goes a long way towards fulfilling the requirements for a Topic Map Query Language (TMQL) and Constraint Language (TMCL), which the Topic Map Community may choose to expend effort on extending. Additionally, OWL DL has a clearly defined formal semantics (Description Logic ref)
    Object
    Topic maps
  4. Pepper, S.; Groenmo, G.O.: Towards a general theory of scope (2002) 0.05 
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    Abstract
    This paper is concerned with the issue of scope in topic maps. Topic maps are a form of knowledge representation suitable for solving a number of complex problems in the area of information management, ranging from findability (navigation and querying) to knowledge management and enterprise application integration (EAI). The topic map paradigm has its roots in efforts to understand the essential semantics of back-of-book indexes in order that they might be captured in a form suitable for computer processing. Once understood, the model of a back-of-book index was generalised in order to cover the needs of digital information, and extended to encompass glossaries and thesauri, as well as indexes. The resulting core model, of typed topics, associations, and occurrences, has many similarities with the semantic networks developed by the artificial intelligence community for representing knowledge structures. One key requirement of topic maps from the earliest days was to be able to merge indexes from disparate origins. This requirement accounts for two further concepts that greatly enhance the power of topic maps: subject identity and scope. This paper concentrates on scope, but also includes a brief discussion of the feature known as the topic naming constraint, with which it is closely related. It is based on the authors' experience in creating topic maps (in particular, the Italian Opera Topic Map, and in implementing processing systems for topic maps (in particular, the Ontopia Topic Map Engine and Navigator.
  5. Garshol, L.M.: Living with topic maps and RDF : Topic maps, RDF, DAML, OIL, OWL, TMCL (2003) 0.05 
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    Object
    Topic maps
  6. Pepper, S.; Moore, G.; TopicMaps.Org Authoring Group: XML Topic Maps (XTM) 1.0 : TopicMaps.Org Specification (2001) 0.05 
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    Abstract
    This specification provides a model and grammar for representing the structure of information resources used to define topics, and the associations (relationships) between topics. Names, resources, and relationships are said to be characteristics of abstract subjects, which are called topics. Topics have their characteristics within scopes: i.e. the limited contexts within which the names and resources are regarded as their name, resource, and relationship characteristics. One or more interrelated documents employing this grammar is called a topic map.TopicMaps.Org is an independent consortium of parties developing the applicability of the topic map paradigm [ISO13250] to the World Wide Web by leveraging the XML family of specifications. This specification describes version 1.0 of XML Topic Maps (XTM) 1.0 [XTM], an abstract model and XML grammar for interchanging Web-based topic maps, written by the members of the TopicMaps.Org Authoring Group. More information on XTM and TopicMaps.Org is available at http://www.topicmaps.org/about.html. All versions of the XTM Specification are permanently licensed to the public, as provided by the Charter of TopicMaps.Org.
    Object
    Topic Maps
  7. Schmitz-Esser, W.; Sigel, A.: Introducing terminology-based ontologies : Papers and Materials presented by the authors at the workshop "Introducing Terminology-based Ontologies" (Poli/Schmitz-Esser/Sigel) at the 9th International Conference of the International Society for Knowledge Organization (ISKO), Vienna, Austria, July 6th, 2006 (2006) 0.05 
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    Content
    Inhalt: 1. From traditional Knowledge Organization Systems (authority files, classifications, thesauri) towards ontologies on the web (Alexander Sigel) (Tutorial. Paper with Slides interspersed) pp. 3-53 2. Introduction to Integrative Cross-Language Ontology (ICLO): Formalizing and interrelating textual knowledge to enable intelligent action and knowledge sharing (Winfried Schmitz-Esser) pp. 54-113 3. First Idea Sketch on Modelling ICLO with Topic Maps (Alexander Sigel) (Work in progress paper. Topic maps available from the author) pp. 114-130
    Object
    Topic maps
  8. Bold, N.; Kim, W.-J.; Yang, J.-D.: Converting object-based thesauri into XML Topic Maps (2010) 0.05 
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    Abstract
    Constructing ontology is considerably time consuming process in general. Since there are a vast amount of thesauri currently available, it may be a feasible solution to exploit thesauri, when constructing ontology in a short period of time. This paper designs and implements a XTM (XML Topic Maps) code converter generating XTM coded ontology from an object based thesaurus. It is an extended thesaurus, which enriches the conventional thesauri with user defined associations, a notion of instances and occurrences associated with them. The reason we adopt XTM is that it is a verified and practical methodology to semantically reorganize the conceptual structure of extant web applications with minimal effort. Moreover, since XTM is conceptually similar to our object based thesauri, recommendation and inference mechanism already developed in our system could be easily applied to the generated XTM ontology. To show that the XTM ontology is correct, we also verify it with onto pia Omnigator and Vizigator, the components of Ontopia Knowledge Suite (OKS) tool.
    Object
    Topic maps
  9. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.02 
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    Date
    26.12.2011 13:22:07
  10. OWL Web Ontology Language Test Cases (2004) 0.01 
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    Date
    14. 8.2011 13:33:22
  11. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.01 
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    Date
    12. 2.2011 17:35:22
  12. Priss, U.: Faceted knowledge representation (1999) 0.01 
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    Date
    22. 1.2016 17:30:31
  13. Definition of the CIDOC Conceptual Reference Model (2003) 0.01 
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    Date
    6. 8.2010 14:22:28
  14. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.01 
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    Date
    26.12.2011 13:40:22
  15. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.01 
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    Date
    3.12.2016 18:39:22
  16. Priss, U.: Description logic and faceted knowledge representation (1999) 0.01 
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    Date
    22. 1.2016 17:30:31
  17. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.01 
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    Date
    28.11.2016 12:43:22
  18. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.01 
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    Date
    16.11.2018 14:22:01

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