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Semantic wikis are very promising tools for producing structured and unstructured data. However, they suffer from a lack of user provided semantic annotations, resulting in a loss of efficiency, despite of their high potential. This paper focuses on an original way to encourage users to annotate semantically pages. We propose a system that suggests automatically computed annotations to users. Users thus only have to validate, complete, modify, refuse or ignore these suggested annotations. We assume that as the annotation task becomes easier, more users will provide annotations. The system we propose is based on collaborative filtering recommender systems, it does not exploit the content of the pages but the usage made on these pages by the users: annotations are deduced from the usage of the pages and the annotations previously provided. The resulting semantic wikis contain several kinds of annotations that are differentiated by their status: human provided annotations, computer provided annotations (suggested by the system), human-computed interactions (suggested by the system and validated by the users) and refused annotations (suggested by the system and refused by the user). Navigation and (semantic) search will thus be facilitated and more efficient.

HUMAN COMPUTER COLLABORATION TO IMPROVE ANNOTATIONS IN SEMANTIC WIKIS