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Improved Search for Socially Annotated Data

Summary: Uses exclusively user-generated tag sequences to perform search and resource ranking. Proposes probabilistic interpolated n-gram models over tag sequences and a scalable constrained optimization framework for training and incremental maintenance, validated on del.icio.us-scale data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9977
Venue
VLDB
Year
2009
Pagerank
4.1905499e-05
Overall Rank
12,361 | 14.10%
DOI
-

Incoming Non-self Citations Over Time

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

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
5,902 Partitioning and Ranking Tagged Data Sources 2013 VLDB 5.2759308e-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
8 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0015436578
2,009 Efficient Network Aware Search in Collaborative Tagging Sites 2008 VLDB 9.8098536e-05
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