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A Probabilistic Model for Linking Named Entities in Web Text with Heterogeneous Information Networks

Summary: SHINE is the first probabilistic model to link web-text named entities to heterogeneous information networks. Entity popularity and an entity object model built from meta-path constrained random walks; meta-path weights learned by EM without training data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4868
Venue
SIGMOD
Year
2014
Pagerank
5.3455323e-05
Overall Rank
8,956 | 38.56%
DOI
10.1145/2588555.2593676

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{shen_sigmod14,
        title = {{A Probabilistic Model for Linking Named Entities in Web Text with Heterogeneous Information Networks}},
        author = {Shen, Wei and Han, Jiawei and Wang, Jianyong},
        series = {{SIGMOD} '14},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2588555.2593676},
        url = {https://dl.acm.org/doi/10.1145/2588555.2593676},
        year = {2014}
}

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
731 PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks 2011 VLDB 0.00014537965
2,647 Building, Maintaining, and Using Knowledge Bases: A Report from the Trenches 2013 SIGMOD 8.2959636e-05
2,829 Linking Temporal Records 2011 VLDB 8.0799603e-05
3,417 DBLP — Some Lessons Learned 2009 VLDB 7.4294642e-05
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