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Who Tags What? An Analysis Framework

Summary: Proposes a dual mining framework for social tagging analysis, using similarity and diversity across users, items, and tags to enable varied analytics. NP-Complete in general; scalable algorithms validated on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10391
Venue
VLDB
Year
2012
Pagerank
4.3965818e-05
Overall Rank
9,100 | 36.70%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,472 Guided Exploration of User Groups 2020 VLDB 5.4888146e-05
7,023 Hear the Whole Story: Towards the Diversity of Opinion in Crowdsourcing Markets 2015 VLDB 4.8576599e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

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