Abstract
In order to obtain a machine understandable semantics for resources, research on the Semantic Web tries to annotate resources with concepts and relations from explicitly defined formal ontologies. This kind of formal annotation is usually done manually or semi-automatically. In this paper, we explore a complement approach that focuses on the annotations of the web which are annotations manually made by normal users without a pre-defined formal ontology. Compared to the formal annotations, although social annotations are coarse-grained, informal and vague, they are also more accessible to more people and better reflect the resources' meaning from the users' point of views during their actual usage of the resources. Using a social bookmark service as an example, we show how emergent semantics [2] can be statistically derived from the social annotations. Furthermore, we apply the derived emergent semantics to discover and search shared bookmarks. The initial evaluation on our implementation shows that our method can effectively discover semantically related bookmarks that current social bookmark service can not discover easily.
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