This new service is based on ClearForest text-analytics solutions. It helps to extract significant phrases from any unstructured text (web documents or office documents). It automatically annotates web content with rich metadata. Any unstructured text can be transformed into an RDF-graph on the fly. Let’s check it out to see how effective it is.
Archive for annotation
I presented this paper in the Semantic Authoring, Annotation and Knowledge Markup Workshop (SAAKM 2007) co-located with the 4th International Conference on Knowledge Capture (K-Cap 2007), Whistler, British Columbia, Canada. It was an interesting workshop followed up by enthusiastic discussions.
Using Data-Extraction Ontologies to Foster Automating Semantic Annotation
Semantic annotation adds formal metadata to web pages to link web data with ontology concepts. Automated semantic annotation is a primary way of enabling the semantic web. A main drawback of existing automated semantic annotation approaches is that they need a post-extraction mapping between extraction categories and ontology concepts. This mapping requirement usually needs human intervention, which decreases automation. Our approach uses data-extraction ontologies to avoid this problem. To automate semantic annotation, the new approach uses an ontology-based data recognizer that fosters automated semantic annotation, optimizes the system performance, provides support for ontology assembly, and is compatible with semantic web standards.
This is partly similar to my project Co-Browse.
In this paper, we report on our experience in building e-coBrowse, an extensible Web co-navigation framework. Extensibility is realized through dynamic content transformation at the HTTP response/request stream level. The framework also provides an API (Application Programming Interface) that gives developers high-level support for creating groupware features. To illustrate the potential of e-coBrowse we developed a number of multi-user browser extensions. The most interesting one is chat-pointer, which allows conferees to simultaneously annotate at mouse-clicked positions inside any Web document. Conferees can comment on shared annotations similar to chat, but with direct visual reference to relevant parts of the document. A characterization of existing approaches for building Web co-navigation systems is also described.
This is a decentralized way of sharing annotations.
This web page gives an introduction about the topic of “Annotation and Authoring for the Semantic Web”. This will include examples and guides for annotation, but also engineering environments for semantic annotation of unstructured content.
KIM is now continuing under the banner of SWAN.
SWAN is an experiment in scaling up automated metadata extraction for industrial strength Semantic Web applications development. The SWAN project leverages language technology to advance a number of existing DERI cluster elements covering both basic research and applications demonstrators. Gartner recently reported that for at least the next decade more than 95% of human-to-computer information input will involve textual language. They also report that by 2012 taxonomic and hierachical knowledge mapping and indexing will be prevalent in almost all information-rich applications. The web revolution has been based largely on human language materials, and in making the shift to the next generation knowledge-based web, human language will remain key.