DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction

Research article (Information Processing & Management, 2024) · cited 13× · AI/ML
Press Enter · cited answer in seconds

DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction

Summary

DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction is a scholarly article[1].

Key Facts

  • DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction's instance of is recorded as scholarly article[2].

📑 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). DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio
MLA “DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio.
BibTeX @misc{4ortxyz_dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction}}, year = {2026}, url = {https://4ort.xyz/entity/dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DyHGTCR-Cas: Learning unified spatio-temporal features based on dynamic heterogeneous graph neural network for information cascade prediction — https://4ort.xyz/entity/dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/dyhgtcr-cas-learning-unified-spatio-temporal-features-based-on-dynamic-heterogeneous-graph-neural-network-for-informatio · Last refreshed: