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Abstract:
This paper pursues the recently emerging paradigm of searching for entities
that are embedded in Web pages. We utilize information extraction techniques to
identify entity candidates in documents, map them onto entries in a richly
structured ontology, and derive a
generalized data graph that encompasses {W}eb pages, entities, and ontological
concepts and relationships. We exploit this combination of pages and entities
for a novel kind of search-result ranking, coined {E}ntity{A}uthority, in order
to improve the quality of keyword queries that return either pages or entities.
To this end, we utilize the mutual reinforcement between authoritative pages
and important entities. This resembles the {HITS} method for Web-graph link
analysis and recently proposed {O}bject{R}ank methods, but our approach
operates on a much richer, typed graph structure with different kinds of nodes
and also differs in the underlying mathematical definitions. Preliminary
experiments with topic-specific slices of Wikipedia demonstrate the
effectiveness of our approach on certain classes of queries.
