Welcome to the Query Answering under Uncertainty in the Semantic Web project website

Both the information on the Web and the number of its human users have been growing exponentially in recent years. For many people, the Web has started to play a fundamental role as a means of providing and searching for information and services. The next revolution in Web search as one of the key technologies of the Web has just started with the incorporation of ideas from the Semantic Web, aiming at transforming current Web search into some form of semantic search and query answering on the Web, by adding meaning to Web contents and queries in the form of an underlying ontology. This also allows for more complex
queries, and for evaluating queries by combining knowledge that is distributed over many Web
pages, i.e., by reasoning over the Web.

This project's central goal is to develop a family of probabilistic data models, along with scalable query answering algorithms, for knowledge bases that are extracted from the Web relative to an underlying ontology, which may serve as the backbone for such next-generation technologies for semantic search and query answering on the Web. We want to realize this by integrating ontology languages, database technologies, and formalisms for managing probabilistic uncertainty.The objectives include developing probabilistic data models, developing algorithms for ranking and query answering, identifying useful scalable fragments, and practically evaluating the results.

Click here for more details of the project