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Interesting-Phrase Mining for Ad-Hoc Text Analytics

Summary: Introduces a phrase-centric framework for ad-hoc text analytics, prioritizing multi-word phrases that are frequent in a subset yet rare in the full corpus. Develops preprocessing, indexing, and top-k search methods for scalable discovery, validated on a large NYT corpus. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10068
Venue
VLDB
Year
2010
Pagerank
4.9629004e-05
Overall Rank
6,684 | 53.51%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
7,912 Mining Quality Phrases from Massive Text Corpora 2015 SIGMOD 4.6183486e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
181 Mining Frequent Patterns without Candidate Generation 2000 SIGMOD 0.00036992674
2,166 BlogScope: A System for Online Analysis of High Volume Text Streams 2007 VLDB 9.3896206e-05
3,256 Multidimensional Content eXploration 2008 VLDB 7.3158557e-05
4,693 Multi-Structural Databases 2005 PODS 5.9955924e-05
6,370 Efficient Implementation of Large-Scale Multi-Structural Databases 2005 VLDB 5.0935585e-05
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