About Ontoba
We are a digital media consultancy with expertise and specialist knowledge in semantic web software and solutions architecture.
We have a proven track record in developing and implementing technical strategy for leading digital media organisations. Our recent experiences have focussed on the development, build and implementation of robust and high performance dynamic semantic publishing systems.
Ontoba provides a range of services from technical strategy, through guidance of your own in-house development team, to delivery of full end-to-end solutions.
Please contact us to discuss your requirements.
Text Analysis and Semantic Annotation
Flat tagging or labelling of content with meta-tags has become common place and is used extensively on blogs and news content to aid search and contextual surfacing of content. Semantic annotation is a relatively simple step further than flat tagging but can add significantly to the utility of applied tags.
Semantic annotation is the application of ontologically modelled references to your digital media content. So instead of simply applying a free text word or phrase as a tag, you apply (associate) to the relevant piece of content a URI reference to an instance of a 'thing' that has been adequately domain modelled.
As an example, if we applied as free text the term "Elvis Presley" to a music article, we would be able to some extent allow users to know that this article was about Elvis Presley, and maybe be able to explore for other articles that have been tagged with the (exact) same phrase. Although if an another article was tagged with "Elvis" there most likely be no correlation between the two terms. If, however, we associated a URI referencing "Elvis Presley" in some ontological domain model to the content, then we also gain all knowledge about Elvis from the underlying model. We can also assert that our instance of Elvis Presley is the same as that of another linked dataset (such as Freebase, MusicBrainz, or DBPedia) thus also be able to surface all the knowledge from those datasets too.
We can provide solutions for text mining, language processing, semantic disambiguation and concept extraction for semantic annotation. If you wish to semantically annotate your text content, Ontoba can help build out fully automatic or semi-automatic solutions for analysing your content for semantic concepts.
We also have considerable expertise in semantic geotagging, and geospatial semantic querying. By annotating content with geospatial semantic metatags, your content can be aggregated both geospatially and semantically. Examples of this would be "Give me all the articles about car accidents within 50 kilometres of London", or "Give me all the political news within the state of New York".