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Mining Quality Phrases from Massive Text Corpora

Summary: Proposes a scalable framework for mining quality phrases from massive text corpora by integrating phrasal segmentation with limited supervision. Demonstrates near-human phrase quality and linear time/space scalability, validated on large corpora. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5149
Venue
SIGMOD
Year
2015
Pagerank
5.4941436e-05
Overall Rank
8,067 | 44.66%
DOI
10.1145/2723372.2751523

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{liu_sigmod15,
        title = {{Mining Quality Phrases from Massive Text Corpora}},
        author = {Liu, Jialu and Shang, Jingbo and Wang, Chi and Ren, Xiang and Han, Jiawei},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2751523},
        url = {https://dl.acm.org/doi/10.1145/2723372.2751523},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
3,467 Multidimensional Content eXploration 2008 VLDB 7.3898968e-05
5,689 Towards the Web of Concepts: Extracting Concepts from Large Datasets 2010 VLDB 6.1205787e-05
7,333 Interesting-Phrase Mining for Ad-Hoc Text Analytics 2010 VLDB 5.6430503e-05
12,152 Scalable Topical Phrase Mining from Text Corpora 2015 VLDB 5.093636e-05
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