Data Cleaning publication categorizer

We tackle the problem of disambiguating entities on the Web. We
propose a user-driven scheme where graphs of entities – represented
by globally identifiable declarative artifacts – self-organize
in a dynamic and probabilistic manner. Our solution has the following
two desirable properties: i) it lets end-users freely define
associations between arbitrary entities and ii) it probabilistically infers
entity relationships based on uncertain links using constraintsatisfaction
mechanisms. We outline the interface between our
scheme and the current data Web, and show how higher-layer applications
can take advantage of our approach to enhance search
and update of information relating to online entities. We describe a
decentralized infrastructure supporting efficient and scalable entity
disambiguation and demonstrate the practicability of our approach
in a deployment over several hundreds of machines.