ai-one inc. has developed an adaptive semantic neural net with semiotic data handling capabilities ( holosemantic SDK/API with libraries) that allows users to quickly analyze and discover meaningful patterns of interleaved text, data, and images.
A range of partner projects are based on ai-one™ technology:
CENDOO Butler is autonomic intelligence to facilitate both creative and logical semiotic data processes In simple terms it's an automated information service that interprets your needs to retrieve specific information that can be tailored for better sense-making. With CENDOO Butler you have learning capabilities that gets smarter with use. And the user - you - have total control over the Butler.
Brainup uses ai-one™ TopicMapper API to mine and understand legacy, archived and current content on your PC, intranet, enterprise data bases or document management systems into your personal knowledge base. For pixel/image data, ASTIS™ Automatic Shoe Track Information System matches and analyzes shoe tracks for crime laboratories. ASTIS has the ability to learn individual forms but also groupings of forms relevant for matching images. It can learn from experience, deal with ambiguity and unknown situations, know when to ask for help, and recover from errors.
The first version of SPARQL provided a standard way to access data on the Semantic Web, and as such was a key enabling technology for the growing Linked Data Web. But the first version of SPARQL lacked some key features for building powerful Semantic Web applications.
SPARQL 1.1, in development since March, 2009, seeks to rectify many of these omissions. SPARQL 1.1 adds an update language, clarifies the relationship between queries and reasoning, specifies a RESTful way to work with RDF data, provides a vocabulary for describing SPARQL endpoints, and, of course, adds several new features to the SPARQL query language, including:
In this panel session, members of the W3C SPARQL Working Group will give an overview of the new features in SPARQL 1.1, along with their motivation, uses, and when you can expect to start using them. (For many, the answer is now!) Following this overview, the Working Group will engage the community in a Q&A session and a discussion of both SPARQL 1.1 and the future of SPARQL beyond 1.1.
Semantics develop when a community uses a common vocabulary to describe the things that matter to them. This talk examines how semantic vocabularies develop, how they are used, how they evolve, and what makes a semantic community sustainable.
We will dissect both formal and informal communities: from the emergent semantics of Twitter and the powerful, lightweight semantics of Wikipedia to the more formal semantics of Freebase schema. These communities represent a diversity of members, continuous evolution, and a wide spectrum of use. This talk will discuss how these factors contribute to the sustainability of the community and the longevity of their semantic practice. The implications for the growth of other semantic communities and the larger Semantic Web will be discussed.
Google announced "Rich Snippets" just over a year ago in May 2009. If webmasters add structured data markup to their web pages, Google can use that data to show better search result descriptions.
In this talk, we'll reflect on what we've been up to in the last year: the adoption rate amongst webmasters, what we've learned, our successes as well as challenges left to be tackled. A particular focus of the talk will be on webmaster participation. What motivates webmasters to add markup? What obstacles do they face? And how do we accelerate the growth of the ecosystem?
New tools emerge every day that apply semantic technologies to text, but what about video? Traditionally video has been seen as a black box for metadata, but this is changing with the emergence of captioning, translation and user tagging. This presentation will look at real world examples of how leading semantic extraction and content APIs, as well as Linked Data sources, are being used to enrich the video viewing experience. ViewChange.org, funded by the Bill & Melinda Gates Foundation, is not only mashing up these APIs, but using them to create social change.