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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.