Embedding knowledge in Web documents
WWW '99 Proceedings of the eighth international conference on World Wide Web
Annotea: an open RDF infrastructure for shared Web annotations
Proceedings of the 10th international conference on World Wide Web
Authoring and annotation of web pages in CREAM
Proceedings of the 11th international conference on World Wide Web
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Creating Semantic Web Contents with Protégé-2000
IEEE Intelligent Systems
MnM: Ontology Driven Semi-automatic and Automatic Support for Semantic Markup
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
S-CREAM - Semi-automatic CREAtion of Metadata
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
CREAM: CREAting metadata for the Semantic Web
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: The Semantic Web: an evolution for a revolution
Towards the self-annotating web
Proceedings of the 13th international conference on World Wide Web
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
From manual to semi-automatic semantic annotation: about ontology-based text annotation tools
Proceedings of the COLING-2000 Workshop on Semantic Annotation and Intelligent Content
A clustering study of a 7000 EU document inventory using MDS and SOM
Expert Systems with Applications: An International Journal
Social knowledge-based recommender system. Application to the movies domain
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Nowadays most of the Web pages contain little amount of structure and supporting information that can reveal their semantics or meanings. To enable automated processing of the Web pages, semantic information such as metadata and tags regarding to each page should be added to it. Several authoring tools have been developed to help users tackling this task. However, manual or semi-automatic authoring is implausible when we intend to annotate large amount of Web pages. In this work, we proposed a method to automatically generate some descriptive metadata and tags for a Web page. The idea is to apply the self-organizing map algorithm to cluster the Web pages and discover the relationships between these clusters. In the mean time, the themes of each cluster are also identified. We then use such relationships and themes to tag the Web pages and generate metadata for the Web pages. The result of experiments shows that our method may generate semantically relevant metadata and tags for the Web pages.