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Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact

Summary: Characterizes three KG generations—entity-based, text-rich, and 'dual neural' KGs that integrate symbolic graphs with LLMs—highlighting unique construction techniques. Distills 'crazy ideas' and an industrialization recipe from research to production and business impact. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13469
Venue
VLDB
Year
2023
Pagerank
5.3483178e-05
Overall Rank
8,921 | 38.80%
DOI
10.14778/3611540.3611636

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{dong_vldb23,
        title = {{Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact}},
        author = {Dong, Xin Luna},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {4130--4137},
        doi = {10.14778/3611540.3611636},
        url = {https://doi.org/10.14778/3611540.3611636},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,243 TIGER: Training Inductive Graph Neural Network for Large-scale Knowledge Graph Reasoning 2024 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

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