SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
On supporting containment queries in relational database management systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Storing and querying ordered XML using a relational database system
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Holistic twig joins: optimal XML pattern matching
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Indexing and Querying XML Data for Regular Path Expressions
Proceedings of the 27th International Conference on Very Large Data Bases
Structural Joins: A Primitive for Efficient XML Query Pattern Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A Prime Number Labeling Scheme for Dynamic Ordered XML Trees
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Incremental maintenance of XML structural indexes
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
ORDPATHs: insert-friendly XML node labels
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
BOXes: Efficient Maintenance of Order-Based Labeling for Dynamic XML Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient structural joins on indexed XML documents
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
From region encoding to extended dewey: on efficient processing of XML twig pattern matching
VLDB '05 Proceedings of the 31st international conference on Very large data bases
XML Document Indexes: A Classification
IEEE Internet Computing
Structural join and staircase join algorithms of sibling relationship
Journal of Computer Science and Technology
Dynamic interval-based labeling scheme for efficient XML query and update processing
Journal of Systems and Software
Efficient updates in dynamic XML data: from binary string to quaternary string
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic Labelling Scheme for XML Data Processing
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part II on On the Move to Meaningful Internet Systems
How to edit gigabyte XML files on a mobile phone with XAS, RefTrees, and RAXS
Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
Indexing and querying XML using extended Dewey labeling scheme
Data & Knowledge Engineering
Efficient labeling scheme for dynamic XML trees
Information Sciences: an International Journal
Dynamically querying possibilistic XML data
Information Sciences: an International Journal
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XML documents are normally stored as plain text files. Hence, the natural and most convenient way to update XML documents is to simply edit the text files. But efficient query evaluation algorithms require XML documents to be indexed. Every element is given a unique identifier based on its location in the document or its preorder-traversal order, and this identifier is later used as (part of) the key in the index. Reassigning orders of possibly a large number of elements is therefore necessary when the original XML documents are updated. Immutable dynamic labeling schemes have been proposed to solve this problem, that, however, require very long labels and may decrease query performance. If we consider a real-world scenario, we note that many relatively small ad-hoc XML segments are inserted/deleted into/from an existing XML database. In this paper, we start from this consideration and we propose a new lazy approach to handle XML updates that also improves query performance. The lazy approach: (i) completely avoids reassigning existing element orders after updates; (ii) improves query processing by taking advantages from segments. Experimental results show that our approach is much more efficient in handling updates than using immutable labeling and, at the same time, it also improves the performance of recently defined structural join algorithms.