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Auto-Grouping Emails For Faster E-Discovery

Summary: Auto-grouping emails for e-discovery via three modes: syntactic near-duplicate clusters, semantic concept-based groups, and thread-aware segmentation. Enron experiments show reduced review time and high precision/recall; integration into IBM eDiscovery Analyzer. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10191
Venue
VLDB
Year
2011
Pagerank
4.1945683e-05
Overall Rank
12,193 | 15.18%
DOI
-

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Rank Cited Paper Year Venue Pagerank
616 Copy Detection Mechanisms for Digital Documents 1995 SIGMOD 0.00019108201
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