VAGUE: a user interface to relational databases that permits vague queries
ACM Transactions on Information Systems (TOIS)
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Answering queries using views with arithmetic comparisons
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
An algorithm for answering queries efficiently using views
ADC '01 Proceedings of the 12th Australasian database conference
A Probabilistic Framework for Vague Queries and Imprecise Information in Databases
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
The Piazza Peer Data Management System
IEEE Transactions on Knowledge and Data Engineering
Plan selection based on query clustering
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Preference SQL: design, implementation, experiences
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Query-answering algorithms for information agents
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A framework for semantic grouping in P2P databases
Information Systems
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Sharing of structured data in P2P overlays is a challenging problem, especially in the absence of a global schema. The nature of structured data stored in the overlay enforces strict methods of querying. However, the intention of the user is usually to obtain information that is semantically relevant to the posed query and not information that strictly complies to structural constraints. The rewriting mechanisms for structured data were initially developed for tasks such as data integration and mediation, which by nature dictate strict consistency. In this work we propose ways of preprocessing a query in order to produce a version that can be rewritten in the classical way. We propose preprocessing guidelines that produce a new query that is most similar to the initially posed query. Accordingly, we discuss thoroughly query similarity aspects from a structural point of view. Finally, we present an algorithm that selects the most appropriate mappings in order to perform query rewriting.