Database Paper Browser

Back to papers

Online Template Induction for Machine-Generated Emails

Summary: Crusher enables online template induction for machine-generated emails. Real-time discovery reduces template delay from weeks to minutes and achieves order-of-magnitude throughput gains over batch systems, while exposing limitations of conventional stream engines for online template induction. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11820
Venue
VLDB
Year
2019
Pagerank
4.1945683e-05
Overall Rank
11,673 | 18.80%
DOI
10.14778/3342263.3342264

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,543 Migrating a Privacy-Safe Information Extraction System to a Software 2.0 Design 2020 CIDR 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

Rank Cited Paper Year Venue Pagerank
142 TelegraphCQ: Continuous Dataflow Processing for an Uncertain World 2003 CIDR 0.00041725802
191 The Design of the Borealis Stream Processing Engine 2005 CIDR 0.00035738595
288 Storm @Twitter 2014 SIGMOD 0.00028939871
314 MillWheel: Fault-Tolerant Stream Processing at Internet Scale 2013 VLDB 0.00028084774
587 Extracting Structured Data from Web Pages 2003 SIGMOD 0.00019648348
824 Twitter Heron: Stream Processing at Scale 2015 SIGMOD 0.0001623129
1,467 SPADE: The System S Declarative Stream Processing Engine 2008 SIGMOD 0.00011849864
2,338 Samza: Stateful Scalable Stream Processing at LinkedIn 2017 VLDB 9.00711e-05
Previous Page 1 / 1 Next

Semantically Similar Papers