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: 3562
Venue: SIGMOD
Year: 2004
Pagerank: 4.5333646e-05
Overall Rank: 8,371 | 41.77%
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
5,712	Flexible and Efficient XML Search with Complex Full-Text Predicates	2006	SIGMOD	5.3584486e-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
1,321	Intelligent Integration of Information	1993	SIGMOD	0.0001261238
3,667	Querying Structured Text in an XML Database	2003	SIGMOD	6.8602249e-05

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12,455	The TopX DB&IR Engine	2007	SIGMOD	4.1945683e-05
3,667	Querying Structured Text in an XML Database	2003	SIGMOD	6.8602249e-05