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STEM: A Spatio-TEmporal Miner for Bursty Activity

Summary: STEM mines spatiotemporal burstiness by jointly extracting bursty time windows and the streams showing them in geo-stamped data. Supports diverse data sources (news, microblogs), end-to-end mining, and a tidy interface for pattern specification. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4622
Venue
SIGMOD
Year
2013
Pagerank
4.1945683e-05
Overall Rank
12,037 | 16.27%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
2,116 On the Spatiotemporal Burstiness of Terms 2012 VLDB 9.5180761e-05
2,166 BlogScope: A System for Online Analysis of High Volume Text Streams 2007 VLDB 9.3896206e-05
2,477 Identifying Similarities, Periodicities and Bursts for Online Search Queries 2004 SIGMOD 8.6941234e-05
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