A Distance-Based Spelling Suggestion Method for XML Keyword Search

Abstract

We study the spelling suggestion problem for keyword search on XML documents. To address the problems in existing work, we propose a distance-based approach to suggesting meaningful query candidates for an issued query. Our approach uses distance to measure the relationship between keyword matching nodes, and ranks a candidate higher if there are closely-related nodes in the database that match the candidate. We design an efficient algorithm to generate top-k query candidates. Experiments with real datasets verified the effectiveness and efficiency of our approach.