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Information Structuring and Retrieval with Topic Maps for Medical E-Learning

Article, was published by Liana Stanescu and Dumitru Burdescu at 2009-10-26

The paper presents original ways of using topic maps for information structuring and retrieval in medical e-learning domain.

External Link: download paper

The paper presents original ways of using topic maps for information structuring and retrieval in medical e-learning domain. The topic map is mainly used for graphical visualization of the MeSH thesaurus containing medical terms. The hierarchical structure of the descriptors from MeSH thesaurus that has also multiple associative and equivalence relationships between medical terms can be properly visualized in this way. The topic map is built and populated using an original algorithm, by mapping an xml file that can be downloaded for free to an xtm file that contains the topic map. The paper also presents how to use the topic map for semantic querying of a multimedia database with medical images that are accompanied by diagnosis and treatment as important information. For retrieving the interest information for student, this access path can be combined with another modern solution: the content-based visual query on the multimedia medical database using primitive features like color and texture.

 

I like the easy but powerful way of merging Topic Maps to extend and combine existing knowledge bases. Thus I see high potential in distributed environments where peer to peer solutions may open the gates to the real Web 3.0.

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Marcel Hoyer
SharpTM
practical-semantics.com
Topic Maps Lab auf der Cebit 2011
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