Improved Search for Socially Annotated Data
Summary: Ranks socially tagged resources via probabilistic interpolated n-gram models of user tag sequences, capturing annotation dynamics beyond flat tag similarity. Scalable constrained optimization enables training and incremental maintenance, validated on million-scale del.icio.us data. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Nikos Sarkas (University of Toronto)
- 2. Gautam Das (University of Texas)
- 3. Nick Koudas (University of Toronto)
BibTeX Citation
@article{sarkas_vldb09,
title = {{Improved Search for Socially Annotated Data}},
author = {Sarkas, Nikos and Das, Gautam and Koudas, Nick},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687715},
url = {https://doi.org/10.14778/1687627.1687715},
year = {2009}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,864 | Partitioning and Ranking Tagged Data Sources | 2013 | VLDB | 5.7510417e-05 |
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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 |
|---|---|---|---|---|
| 5 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0010828372 |
| 2,200 | Efficient Network-Aware Search in Collaborative Tagging Sites | 2008 | VLDB | 8.9664473e-05 |
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