XClean: Providing valid spelling suggestions for XML keyword queries

Y. Lu, W. Wang, Jianxin Li, C. Liu

Research output: Chapter in Book/Conference paperConference paper

17 Citations (Scopus)

Abstract

An important facility to aid keyword search on XML data is suggesting alternative queries when user queries contain typographical errors. Query suggestion thus can improve users' search experience by avoiding returning empty result or results of poor qualities. In this paper, we study the problem of effectively and efficiently providing quality query suggestions for keyword queries on an XML document. We illustrate certain biases in previous work and propose a principled and general framework, XClean, based on the state-of-the-art language model. Compared with previous methods, XClean can accommodate different error models and XML keyword query semantics without losing rigor. Algorithms have been developed that compute the top-k suggestions efficiently. We performed an extensive experiment study using two large-scale real datasets. The experiment results demonstrate the effectiveness and efficiency of the proposed methods. © 2011 IEEE.
Original languageEnglish
Title of host publication2011 IEEE 27th International Conference on Data Engineering (ICDE)
EditorsSerge Abiteboul , Christoph Koch , Kian-Lee Tan, Alfons Kemper , Wolfgang Nejdl
Place of PublicationGermany
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages661-672
Number of pages12
ISBN (Print)9781424489589
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE 27th International Conference on Data Engineering (ICDE) - Hannover, Germany
Duration: 11 Apr 201116 Apr 2011

Conference

Conference2011 IEEE 27th International Conference on Data Engineering (ICDE)
CountryGermany
CityHannover
Period11/04/1116/04/11

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  • Cite this

    Lu, Y., Wang, W., Li, J., & Liu, C. (2011). XClean: Providing valid spelling suggestions for XML keyword queries. In S. Abiteboul , C. Koch , K-L. Tan, A. Kemper , & W. Nejdl (Eds.), 2011 IEEE 27th International Conference on Data Engineering (ICDE) (pp. 661-672). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDE.2011.5767847