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Mining Significant Semantic Locations From GPS Data

Summary: Graph-based framework to mine semantic locations from GPS traces, modeling location-location and location-user links. Mutual reinforcement via random walks ties significance to user authority, visits, durations, and travel distance, scalable to 100M GPS records. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10146
Venue
VLDB
Year
2010
Pagerank
5.3005017e-05
Overall Rank
5,851 | 59.34%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,821 STMaker - A System to Make Sense of Trajectory Data 2014 VLDB 6.726077e-05
9,048 On Repairing Timestamps for Regular Interval Time Series 2022 VLDB 4.3997447e-05
9,659 Hyper-Local, Directions-Based Ranking of Places 2011 VLDB 4.3067693e-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.

Rank Cited Paper Year Venue Pagerank
263 OPTICS: Ordering Points To Identify the Clustering Structure 1999 SIGMOD 0.00029955858
320 ObjectRank: Authority-Based Keyword Search in Databases 2004 VLDB 0.00027574254
2,020 Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects 2009 VLDB 9.7766925e-05
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