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: h111f65739388b26b
Venue: SIGMOD
Year: 2004
Pagerank: 5.2707392e-05
Overall Rank: 8,816 | 40.73%
DOI: 10.1145/1007568.1007649

Incoming Non-self Citations Over Time

Authors

1. Edward Hung (University of Maryland)
2. Yu Deng (University of Maryland)
3. V.S. Subrahmanian (University of Maryland)

BibTeX Citation

@inproceedings{hung_sigmod04,
        title = {{TOSS: An Extension of TAX with Ontologies and Similarity Queries}},
        author = {Hung, Edward and Deng, Yu and Subrahmanian, V.S.},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007649},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007649},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,273	Flexible and Efficient XML Search with Complex Full-Text Predicates	2006	SIGMOD	5.8278142e-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
1,611	Intelligent Integration of Information	1993	SIGMOD	0.00010073084
3,810	Querying Structured Text in an XML Database	2003	SIGMOD	7.0088933e-05

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