The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Text databases: a survey of text models and systems
ACM SIGMOD Record
A language for queries on structure and contents of textual databases
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Proximal nodes: a model to query document databases by content and structure
ACM Transactions on Information Systems (TOIS)
Integrating contents and structure in text retrieval
ACM SIGMOD Record
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Indexed Tree Matching with Complete Answer Representations
PODDP '98 Proceedings of the 4th International Workshop on Principles of Digital Document Processing
ACM Transactions on Information Systems (TOIS)
Journal of the American Society for Information Science and Technology - XML
Towards Aggregated Answers for Semistructured Data
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Anatomy of a native XML base management system
The VLDB Journal — The International Journal on Very Large Data Bases
Searching structured documents
Information Processing and Management: an International Journal
Choosing document structure weights
Information Processing and Management: an International Journal
LSDX: a new labelling scheme for dynamically updating XML data
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
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Structured document retrieval has established itself as a new research area in the overlap between Database Systems and Information Retrieval. This work proposes a filtering technique, that can be added to already existing index structures of many structured document retrieval systems. This new technique takes the contextual structure information of query and document database into account and reduces the occurrence sets returned by the original index structure drastically. This improves the performance of query evaluation. A measure is introduced that allows to quantify the added value of the proposed index structure. Based on this measure a heuristic is presented that allows to include only valuable context information in the index structure.