Spelling Suggestion for XML Keyword Search Based on XSketch Synopsis

Authors:
Sheng Li;Junhu Wang
Affiliations:
School of Information and Communication Technology, Griffith University, Gold Coast Campus Australia;School of Information and Communication Technology, Griffith University, Gold Coast Campus Australia
Venue:
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Year:
2013

Citing 9
Cited 0

Statistical synopses for graph-structured XML databases

Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Selectivity Estimation for XML Twigs

ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Approximate XML query answers

SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Effective keyword-based selection of relational databases

Proceedings of the 2007 ACM SIGMOD international conference on Management of data
XSeek: a semantic XML search engine using keywords

VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Nearest keyword search in XML documents

Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
XClean: Providing valid spelling suggestions for XML keyword queries

ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Spelling suggestion for XML keyword search based on pairwise keyword summaries

WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
A distance-based spelling suggestion method for XML keyword search

ER'12 Proceedings of the 31st international conference on Conceptual Modeling

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study the spelling suggestion problem for XML keyword search, which provides users with alternative queries that may better express users' search intention. In order to return the suggested queries more efficiently, we evaluate the quality of the query by estimating the selectivity and quality of each query pattern. The selectivity estimation is based on the XSketch synopsis, which summarizes the structure and value distribution of the original XML data source. We propose an approach to generating the top-K query candidates. Experiments with real datasets verifies the effectiveness and efficiency of our approach.