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1、,1,Semantic Annonation,2,Content,Semantic Annotation Overview Implements of Semantic Annotation Related Research Conclution,3,Why Semantic Annotation?,Semantic Web is about adding formal semantics (metadata, knowledge) to the web content for the purpose of more efficient access and management. Since
2、 its vitality depends on the presence of critical mass of metadata, the acquisition of this metadata is a major challenge for the Semantic Web community.,4,Why Semantic Annotation?,To realize this, the creation of semantic annotation, the linking of web pages to ontologies must become automatic or s
3、emi automatic process.,6,Progress of Semantic Annotation,Prerequisite for representation of semantic annotation: Ontology defining the entity classes. Entity identifier Knowledge base with entity descriptions Information Extraction(Named Entity Recognition) Indexing and Retrieval,7,Ontology for Sema
4、nti Annotation,Light-weight Upper Level Ontology Address number of general classes which use to appear in texts in various domains Using RDF(S) to express the Upper Light-weight Upper Level Ontology is sufficient. In order to allow easy extension towards OWL,8,Requirements of Metadata Encoding and M
5、anagement,Documents in different formats to be identifiable and their text content to be accessible; To allow non-embedded annotations over documents to be stored, managed and retrieved according to their positions, features, and references to a KB; To allow embedding of the annotations at least for
6、 some of the formats; To allow export and exchange of the annotations in different formats Example:TEI5 and Tipster6,9,Entity Descriptions(Knowledge Base, KB),To identify, describe and interconnect the entities in a general, flexible and standard fashion. Two sorts of entity knowledge Pre-populated:
7、extend the ontology to match the appliance domain, spicific entities. Automatically extracted: use advantage of IE to enrich the KB.,10,Information Extraction(IE),Information Extraction is a technology based on analyzing natural language in order to extract snippets of information. It involves natur
8、al language process and named entity recognition. Reuse of existing systems to implement an ontology-based infrastructure for IE.,11,Indexing and Retrieval,Based on semantic annotations, efficient indexing and retrieval techniques could be developed involving explicit handling of the named entity re
9、ferences. Given metadata indexing of the content, advanced semantic querying should be feasible. semantic annotations could be used to match specific references in the text to more general queries.,12,Applications,Highlighting Semantic search Categorization Generation of more advanced metadata Smoot
10、h traversal between unstructured text and formal knowledge,13,Implements of Semantic Annotation,Three kinds of platforms: Manual Semi-automatic Full-automatic Due to some researcheres, manual annotation is no longer fit the semantic annotation. There is not yet possible to implement full automatic.,
11、14,Platform Classification,Semantic annotation platforms(SAPs) can be classified based on the type of annotation method used. Pattern-based Machine Learning-based Multistrategy,15,Platform Classification,Pattern-based AeroDAML Armadillo KIM MUSE SemTag,Machine Learning-based MnM Ont-O-Mat:Amilcare,1
12、6,17,Summary of SAPs,SAPss annotation methods have the largest impact on the effectiveness of semantic annotation. The two primary approaches are pattern-based and machine learning-based. Machine learning algorithms often perform more effectively than pattern-based methods, but the MUSE system shows
13、 that a rule-based system using conditional processing can perform as well as a machine learning system.,18,Related Research,Atanas Kiryakov KIM(Knowledge and Information Management) OWLIM, a family of semantic repositories. Semantic Biomedical Tagger Michael Sintek Competence Center Semantic Web De
14、velop tools for industry,commerce and government, identifying potential exploitation of R&D results,19,Related Research,Bernhard Schandl Semantic multimedia annotation Ricercatore Machine learning & knowledge discovery on semantic web KMi Annotaion on videos,20,Conclusion,Semantic annotation is a in
15、termediate result from traditional web and semantic web. It is useful to implement some semantic web services. Using the exiting platforms, the development task will become less difficult.,21,Idea,In the domain of educational information, information discovery is a major problem for ordinary users. By collecting the information from the web, using a special ontology of the domain, then implement semantic retrieval or search with the semantic annotation.,
