Authors:
Anne Boyer
;
Armelle Brun
and
Hala Skaf-Molli
Affiliation:
LORIA-Nancy Université, France
Keyword(s):
Recommender systems, Semantic wikis, Automatic annotation.
Related
Ontology
Subjects/Areas/Topics:
Data Engineering
;
Ontologies and the Semantic Web
;
Ontology and the Semantic Web
;
User Modeling
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Personalization
Abstract:
Semantic wikis are 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. We propose a system that suggests automatically computed annotations to users in peer to peer semantic wikis. Users only have to validate, complete, modify, refuse or ignore these suggested annotations. Therefore, the annotation task becomes easier, more users will provide annotations. The system 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. The resulting semantic wikis contain several kinds of annotations with different status: human, computer or human-computed provided annotations.