A graphical query language supporting recursion
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Fast text searching: allowing errors
Communications of the ACM
SIAM Journal on Computing
Flexible queries over semistructured data
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The complexity of acyclic conjunctive queries
Journal of the ACM (JACM)
Approximating Terminological Queries
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
Proceedings of the 15th international conference on World Wide Web
Engineering Label-Constrained Shortest-Path Algorithms
AAIM '08 Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management
Using Similarity Metrics for Matching Lifelong Learners
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Ranking Approximate Answers to Semantic Web Queries
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Using annotations from controlled vocabularies to find meaningful associations
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
Preferentially annotated regular path queries
ICDT'07 Proceedings of the 11th international conference on Database Theory
Robust query processing for personalized information access on the semantic web
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
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We consider the problem of finding and ranking paths in semistructured data without necessarily knowing its full structure. The query language we adopt comprises conjunctions of regular path queries, allowing path variables to appear in the bodies and the heads of rules, so that paths can be returned to the user. We propose an approximate query matching semantics which adapts standard notions of approximation from string matching to graph matching. Query results are returned to the user ranked in order of increasing "distance" to the user's original query. We show that the top-k approximate answers can be returned in polynomial time in the size of the database graph and the query.