ROSeAnn: Reconciling Opinions of Semantic Annotators

Summary: ROSeAnn reconciles diverse semantic-annotation opinions via a unified view over multiple annotators on text and Web documents. It uses ontology-aware aggregation, with supervised and unsupervised (weighted-repair) methods to resolve conflicts and merge annotations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10770
Venue: VLDB
Year: 2013
Pagerank: 5.093636e-05
Overall Rank: 12,266 | 15.85%
DOI: 10.14778/2536274.2536285

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Luying Chen (University of Oxford)
2. Stefano Ortona (University of Oxford)
3. Giorgio Orsi (University of Oxford)
4. Michael Benedikt (University of Oxford)

BibTeX Citation

@article{chen_vldb13,
        title = {{ROSeAnn: Reconciling Opinions of Semantic Annotators}},
        author = {Chen, Luying and Ortona, Stefano and Orsi, Giorgio and Benedikt, Michael},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {12},
        pages = {1238},
        doi = {10.14778/2536274.2536285},
        url = {https://doi.org/10.14778/2536274.2536285},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
12,282	Aggregating Semantic Annotators	2013	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
65	Freebase: A Collaboratively Created Graph Database For Structuring Human Knowledge	2008	SIGMOD	0.00038697603

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