In this project, we are developing an approach for identifying and exposing the latent semantics within a folksonomy, which will enable a new class of data integration applications. We have previously developed software enabling non-programmers to create web feeds, and an “Intelligence Portal” system for displaying that data in an integrated view. The new application we are developing in this project will enable domain-experts to automatically integrate webfeeds into the portal without any programming being required. To achieve this, we will be investigating an approach that enables an expert to train the system to perform the integration task. The training process is very efficient, because the system automatically induces background concepts and relations based on a folksonomy, which in turn boosts its performance.
Keywords: Machine Learning, Folksonomy, Artificial Intelligence, Relational Learning, Information Extraction From The Web, Information Integration
