MPI-I-2007-5-001. March 2007, 42 pages. | Status: available - back from printing | Next --> Entry | Previous <-- Entry
Abstract in LaTeX format:
The Web has the potential to become the world's largest knowledge base.
In order to unleash this potential, the wealth of information available on the
web needs to be extracted and organized. There is a need for new querying
techniques that are simple yet more expressive than those provided by
standard keyword-based search engines. Search for knowledge rather than Web
pages needs to consider inherent semantic structures like entities (person,
organization, etc.) and relationships (isA, locatedIn, etc.).
In this paper, we propose NAGA, a new semantic search engine. NAGA's
knowledge base, which is organized as a graph with typed edges, consists of
millions of entities and relationships automatically extracted fromWeb-based
corpora. A query language capable of expressing keyword search for the casual
user as well as graph queries with regular expressions for the expert,
enables the formulation of queries with additional semantic information. We
introduce a novel scoring model, based on principles of generative language
models, which formalizes several notions like confidence, informativeness and
compactness and uses them to rank query results. We demonstrate NAGA's
superior result quality over current search engines by conducting a
comprehensive evaluation, including user assessments, for advanced queries.
References to related material:
|To download this research report, please select the type of document that fits best your needs.||Attachement Size(s):|
|Please note: If you don't have a viewer for PostScript on your platform, try to install GhostScript and GhostView|