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Content archived on 2024-05-18

Visual Contextualisation of Digital Content

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Digital content becomes more comprehensive

In the quest of better understanding the digital content on the Internet, the VICODI project developed the Context Engine prototype for innovative textual and visual contextualisation.

The effective formalisation of the generic concept of context is one of the most difficult tasks for IT researchers and most efforts focus on smaller subsets of this theory. As specified by Wurman's approach, contextualisation involves Location, Alphabetical order, Time, Category and Hierarchy (LATCH). On the basis of the LATCH approach, the VICODI project exploited ontological markup and knowledge authoring tools in order to provide for Category and Hierarchy. In addition, cartographic maps were employed for Location context and thesauri for historical information for experimenting with temporal contextualisation in the field of European History. Part of the project's work included the development of the Context Engine prototype for combining contextualisation of textual and graphical resources. More specifically, this innovation comprises a transformation engine for generating contextualised textual resources and supporting visualisations based on XML data, such as the Scalable Vector Graphic (SVG) historical maps. The Context Engine involves a server that allows the transformation of training data into suitable correlation vectors to describe relationships between system entities, such as concepts or instances. Apart from training, the server additionally supports vector similarity functionalities, including term-term, term-document and document-document. Top-ranking concepts like location, category, person, event, artefact, abstract notion and social organisation are also recorded along with ontology entities. Furthermore, the prototype also includes a client that employs the context of the dynamically derived or recorded resource and the ontology to realise LATCH logical process. For instance, historical map queries can be narrowed in order to predict the major locations, categories and time periods, using a wider interval for user reference. The advanced Context Engine allows integration of standard information retrieval procedures with knowledge or ontology based retrieval mechanisms. Although it has been created for the purposes of the VICODI system, it is platform independent as it has been developed in Java. Various sorts of collaboration are sought in the fields of knowledge and semantic web applications, as well as, visualisation support, e-Learning and cultural heritage. For further information click at: http://www.vicodi.org/