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.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.
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Conference Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
7532 LNCS
Publisher URI
Subject
Information retrieval and web search
Information and computing sciences