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A Temporal Context-Aware Model for User Behavior Modeling in Social Media Systems

Summary: Proposes TCAM, a temporal-context-aware latent model for social-media user behavior that jointly models intrinsic-interest and temporal-context topics. An item-weighting scheme and efficient online query processing enable fast scalable recommendations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4815
Venue
SIGMOD
Year
2014
Pagerank
4.4937074e-05
Overall Rank
8,544 | 40.57%
DOI
10.1145/2588555.2593685

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,439 TencentRec: Real-time Stream Recommendation in Practice 2015 SIGMOD 6.1885354e-05
11,834 Topic Exploration in Spatio-Temporal Document Collections 2016 SIGMOD 4.1945683e-05
11,846 Real-time Video Recommendation Exploration 2016 SIGMOD 4.1945683e-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
7 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0015496097
5,015 Challenging the Long Tail Recommendation 2012 VLDB 5.7584513e-05
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