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)
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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 |
|---|---|---|---|---|
| 2,117 | On the Spatiotemporal Burstiness of Terms | 2012 | VLDB | 9.5088574e-05 |
| 2,171 | BlogScope: A System for Online Analysis of High Volume Text Streams | 2007 | VLDB | 9.3805639e-05 |
| 2,478 | Identifying Similarities, Periodicities and Bursts for Online Search Queries | 2004 | SIGMOD | 8.6866662e-05 |
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