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Differentially private frequent sequence mining via sampling-based candidate pruning

Research article (2015 IEEE 31st International Conference on Data Engineering, 2015) · cited 27× · AI/ML
CreativeWork academia

Facts

3 properties
Instance of
scholarly article[2]
Publication date
April 1, 2015as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
Title
Differentially private frequent sequence mining via sampling-based candidate pruningas of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 3
OpenAlex ID
W1606520508as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
DOI
10.1109/ICDE.2015.7113354as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
PubMed publication ID
26973430as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded

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📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Authored by 4
Li Xiong, Sen Su, Shengzhi Xu, Zhengyi Li
← Author of 4
Li Xiong, Sen Su, Shengzhi Xu, Zhengyi Li
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Summary

Differentially private frequent sequence mining via sampling-based candidate pruning is a scholarly article[1].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Differentially private frequent sequence mining via sampling-based candidate pruning. Retrieved October 14, 2026, from https://4ort.xyz/entity/differentially-private-frequent-sequence-mining-via-sampling-based-candidate-pruning
MLA “Differentially private frequent sequence mining via sampling-based candidate pruning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 14 Oct. 2026, https://4ort.xyz/entity/differentially-private-frequent-sequence-mining-via-sampling-based-candidate-pruning.
BibTeX @misc{4ortxyz_differentially-private-frequent-sequence-mining-via-sampling-based-candidate-pruning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Differentially private frequent sequence mining via sampling-based candidate pruning}}, year = {2026}, url = {https://4ort.xyz/entity/differentially-private-frequent-sequence-mining-via-sampling-based-candidate-pruning}, note = {Accessed: 2026-10-14}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Differentially private frequent sequence mining via sampling-based candidate pruning — https://4ort.xyz/entity/differentially-private-frequent-sequence-mining-via-sampling-based-candidate-pruning (retrieved 2026-10-14)

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