Download Free PDF. Enrico Motta. A short summary of this paper. Download Download PDF. Translate PDF. OpenKnowledge FP D8. This introduces a number of improvements to its performance and user interface and also integrates with the latest version of the architecture for 'Cautious Knowledge Sharing' CKS ,which is described in Deliverable 8.
Here, we also perform a small evaluation of the integration of PowerMagpie with the CKS architecture, which shows that while untyped individuals are not retrieved in the current CKS framework, automatic typing of individuals yields In deliverable D8. The queries are then routed through an additional node, called the DescriptionRepository, which only sends them to the rel- evant peers i. This second integration scenario was evaluated with PowerAqua by compar- ing its performance with that achieved by using the standard centralised Watson repository.
In this deliverable we apply the same scenario to the PowerMagpie ap- plication. More precisely, we evaluate the differences in the performance of the tool when broadcasting queries to all the peers, and when routing them through the DescriptionRepository.
Since PowerMagpie has a dif- ferent query profile adapted to its specific knowledge needs, we expect to obtain different results, providing additional insights on the approach. The rest of this document is organised as follows: in Section 2 we highlight the key features of PowerMagpie and the improvements made to the tool with respect to the version presented in deliverable D8.
Section 3 describes the evaluation, while the main conclusions from this work are presented in Section 4. From a user perspective, PowerMagpie is an extension of a classical web browser and takes the form of a narrow, vertical widget displayed on top of the currently browsed web page. This widget provides several func- tionalities that support the exploration of relevant semantic information. Each term can be extended to display the semantic information i. Each ontology in the panel can be opened up to explore the semantic entities matching terms of the page.
Navigation mechanisms are provided from the semantic entities in PowerMagpie to their occurrences in the text, and from the text to semantic entities. While this first prototype gave us an insight in the potential of this paradigm, it lacked real-time responsiveness.
Thus, in deliverable D8. Solutions were devised to reduce the scope of the queries from PowerMagpie to external services Watson and Google , to improve the identification of key terms in the page and their rank- ing, and to reduce the overhead due to the communication with Watson and the OpenKnowledge P2P network. Additionally, the D8. Deliverable D8. The PowerMagpie entity panel.
The PowerMagpie ontology panel. In particular, several improvements have been made to tackle performance issues and reduce response time; and to provide more usable interfaces for displaying semantic information and supporting semantic navigation. Concerning performance improvements, one of the bottlenecks that was identified previously concerned the identification of key terms in the web page. However, this method was often extracting unnecessary long lists of terms, failing to distinguish between terms really significant to the domain of the webpage, and terms that were just statistically significant.
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Inspired by the Semantic Web , Genyris presents a new programming paradigm. Objects can belong to multiple classes independant from construction. Indentation reduces parentheses yet retains the power of Lisp. External Java libraries can be imported. This library provides a thin abstraction layer over the Redland librdf library. Please note that this code is at the prototyping phase.
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