We study query processing in large graphs that are fundamental data model underpinning various social networks and Web structures. Given a set of query nodes, we aim to find the g...
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
Information extraction from text databases is a useful paradigm to populate relational tables and unlock the considerable value hidden in plain-text documents. However, information...
Classical retrieval models support content-oriented searching for documents using a set of words as data model. However, in hypertext and database applications we want to consider...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...