Expressive and flexible access to web-extracted data
Jeffrey Pound, Ihab F. Ilyas, Grant Weddell · 2010
Automated extraction of structured data from Web sources often leads to large heterogeneous knowledge bases (KB), with data and schema items numbering in the hundreds of thousands or millions. Formulating information needs with conventional structured query languages is difficult due to the sheer size of schema information available to the user. We address this challenge by proposing a new query language that blends keyword search with structured query processing over large information graphs with rich semantics. Our formalism for structured queries based on keywords combines the flexibility of keyword search with the expressiveness of structures queries.