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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Evaluation of a Self-adapting Method for Resource Classification in Folksonomies
verfasst von : José Javier Astrain, Alberto Córdoba, Francisco Echarte, Jesús Villadangos
Erschienen in: 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing
Verlag: Springer Berlin Heidelberg
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Nowadays, folksonomies are currently the simplest way to classify information inWeb 2.0. However, such folksonomies increase continuously their amount of information without any centralized control, complicating the knowledge representation. We analyse a method to group resources of collaborative-social tagging systems in semantic categories. It is able to automatically create the classification categories to represent the current knowledge and to self-adapt to the changes of the folksonomies, classifying the resources under categories and creating/deleting them. As opposed to current proposals that require the re-evaluation of the whole folksonomy to maintain updated the categories, our method is an incremental aggregation technique which guarantees its adaptation to highly dynamic systems without requiring a full reassessment of the folksonomy.