TOSS: An Extension of TAX with Ontologies and Similarity Queries

Summary: Extends TAX for XML query processing with similarity-aware ontologies (SEO) to recover recall lost due to term semantics. Introduces an SEO-augmented algebra, defines answer quality as sqrt(precision×recall), and shows competitive results on DBLP and SIGMOD datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3563
Venue: SIGMOD
Year: 2004
Pagerank: 4.5289973e-05
Overall Rank: 8,369 | 41.84%
DOI: -

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,722	Flexible and Efficient XML Search with Complex Full-Text Predicates	2006	SIGMOD	5.3534445e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,319	Intelligent Integration of Information	1993	SIGMOD	0.00012608305
3,671	Querying Structured Text in an XML Database	2003	SIGMOD	6.853634e-05

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9,890	SOR: A Practical System for Ontology Storage, Reasoning and Search	2007	VLDB	4.2576366e-05
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8,244	Optimizing Query Answering under Ontological Constraints	2011	VLDB	4.5464433e-05
3,046	An Efficient and Versatile Query Engine for TopX Search	2005	VLDB	7.6586679e-05
12,464	The TopX DB&IR Engine	2007	SIGMOD	4.1905499e-05
3,671	Querying Structured Text in an XML Database	2003	SIGMOD	6.853634e-05