An Extensible Framework to Sort out Nodes in Graph-Based Structures Powered by the Spreading Activation Technique: The ONTOSPREAD Approach
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Semantic Web
Knowledge-Management
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Editorial:
Miltiadis D. Lytras
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Resumen:
This paper presents an extensible framework for the Spreading Activation technique. This technique is supported by the ONTOSPREAD framework enabling the development, configuration, customization, and execution of the Spreading Activation method on graph-based structures. It has been used for a long time to the efficient exploration of knowledge bases built on semantic networks in Information and Document Retrieval domains. The emerging Web of Data and the sheer mass of information now available make it possible the deployment of new services and applications based on the reuse of existing vocabularies and datasets. A large amount of this information is published using semantic web languages and formats such as RDF, implicit graph structures developed using W3C standard languages; but new flexible and scalable methods to create added-value services and exploit the data are required. That is why ONTOSPREAD is considered relevant in providing a new way to implement the double process of activation and spreading of concepts in graph-based structures, more specifically to browse and rank resources in the Web of Data realm. The original constraints like weight degradation according to the distance are provided in combination with others coming from the extension of this technique like the converging paths reward. Finally an evaluation methodology and two examples using the well-known ontologies GALEN and SNOMED CT are presented to validate the goodness, the improvement, and the capabilities of this technique.
This paper presents an extensible framework for the Spreading Activation technique. This technique is supported by the ONTOSPREAD framework enabling the development, configuration, customization, and execution of the Spreading Activation method on graph-based structures. It has been used for a long time to the efficient exploration of knowledge bases built on semantic networks in Information and Document Retrieval domains. The emerging Web of Data and the sheer mass of information now available make it possible the deployment of new services and applications based on the reuse of existing vocabularies and datasets. A large amount of this information is published using semantic web languages and formats such as RDF, implicit graph structures developed using W3C standard languages; but new flexible and scalable methods to create added-value services and exploit the data are required. That is why ONTOSPREAD is considered relevant in providing a new way to implement the double process of activation and spreading of concepts in graph-based structures, more specifically to browse and rank resources in the Web of Data realm. The original constraints like weight degradation according to the distance are provided in combination with others coming from the extension of this technique like the converging paths reward. Finally an evaluation methodology and two examples using the well-known ontologies GALEN and SNOMED CT are presented to validate the goodness, the improvement, and the capabilities of this technique.
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