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D(k)-index: an adaptive structural summary for graph-structured data
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Source International Conference on Management of Data archive
Proceedings of the 2003 ACM SIGMOD international conference on Management of data table of contents
San Diego, California
SESSION: XML indexing and compression table of contents
Pages: 134 - 144  
Year of Publication: 2003
ISBN:1-58113-634-X
Authors
Qun Chen  National University of Singapore, Singapore
Andrew Lim  National University of Singapore, Singapore
Kian Win Ong  National University of Singapore, Singapore
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 19,   Downloads (12 Months): 138,   Citation Count: 34
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ABSTRACT

To facilitate queries over semi-structured data, various structural summaries have been proposed. Structural summaries are derived directly from the data and serve as indices for evaluating path expressions on semi-structured or XML data. We introduce the D(k) index, an adaptive structural summary for general graph structured documents. Building on previous work, 1-index and A(k) index, the D(k)-index is also based on the concept of bisimilarity. However, as a generalization of the 1-index and A(k)-index, the D(k) index possesses the adaptive ability to adjust its structure according to the current query load. This dynamism also facilitates efficient update algorithms, which are crucial to practical applications of structural indices, but have not been adequately addressed in previous index proposals. Our experiments show that the D(k) index is a more effective structural summary than previous static ones, as a result of its query load sensitivity. In addition, update operations on the D(k) index can be performed more efficiently than on its predecessors.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  34

Collaborative Colleagues:
Qun Chen: colleagues
Andrew Lim: colleagues
Kian Win Ong: colleagues