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A framework to specify, extract and manage topic maps driven by ontology
Paper, was published by Giovani Rubert Librelotto, Pedro Rangel Henriques, and José Carlos Ramalho at 2008-09-24
External Links: download paper and ACM record
The ability to extract and merge data that from documents (or databases) of different types, in order to acquire knowledge from a vast repository of information, is of unquestionable value. However that desirable integration is not an easy task. Different approaches can be followed to achieve it, ranging from the merge of resources (implying their conversion to a common format) till the fusion of the extracted parts. The idea is to interoperate those resources keeping them independent, without changes or transformations, creating over them an integration layer that gives us a general overview, as the information slices were gathered. This is possible creating a semantic network, or a conceptual map, over the resources, which relates data items among them mapping each one to its different occurrences in the repository; formally speaking, that conceptual map corresponds to the ontology that describes the knowledge we want to acquire. In this paper, we introduce Metamorphosis, a Topic Maps oriented environment to extract data from heterogeneous information repositories and to generate a browser and conceptual navigator for the extracted knowledge.
Authors
Giovani Rubert Librelotto
http://www-usr.inf.ufsm.br/~librelotto/
Giovani Rubert is project leader of Metamorphosis and Ontocancro.
Projects
Metamorphosis
is a {{project}}.
Nowadays, data handled by an institution or company is spread out by more than one database and lots of documents of different types. To extract the ...
Visit homepage of Metamorphosis
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Topic Maps aware search adds an important and efficient access path both to information, and to the knowledge represented in our application systems.