Ontology-Based Spelling Suggestion for RDF Keyword Search

Abstract

We study the spelling suggestion problem for keyword search over RDF data, which provides users with alternative queries that may better express users' search intention. In order to return the suggested queries more efficiently, we utilize the ontology information to reduce the search space of query candidates and facilitate the generation of suggested queries. Experiments with real datasets show the effectiveness and efficiency of our approach.