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APEX: an adaptive path index for XML data
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Statistical synopses for graph-structured XML databases
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
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ICDT '97 Proceedings of the 6th International Conference on Database Theory
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VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
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FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
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Structure and value synopses for XML data graphs
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SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
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Compact reachability labeling for graph-structured data
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Information Systems
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VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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Ph.D. '08 Proceedings of the 2008 EDBT Ph.D. workshop
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ACM Transactions on Database Systems (TODS)
Incremental sequence-based frequent query pattern mining from XML queries
Data Mining and Knowledge Discovery
Query Optimization for Complex Path Queries on XML Data
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Xistree: bottom-up method of XML indexing
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SAM: an efficient algorithm for F&B-index construction
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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.