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word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data

Summary: Surveys practical embedding methods for graphs and relational structures and frames the field as lacking foundational theory. Proposes two formal approaches to characterize expressivity and limitations of vector embeddings, links existing techniques to them, and suggests future directions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1804
Venue
PODS
Year
2020
Pagerank
0.00010852334
Overall Rank
1,411 | 90.33%
DOI
10.1145/3375395.3387641

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{grohe_pods20,
        address = {New York, NY, USA},
        series = {{PODS} '20},
        title = {{word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data}},
        url = {https://dl.acm.org/doi/10.1145/3375395.3387641},
        doi = {10.1145/3375395.3387641},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Grohe, Martin},
        year = {2020}
}

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