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Jieming Shi

12 papers hereh-index 19996 citations44 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author7
  • last author3

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • cs.SI7
  • cs.LG3
  • cs.DB2
same name
  • Jieming Shi — 11 papers, h 7
  • Jieming Shi — 1 paper, h 1
  • Jieming Shi — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192024
most citedA Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation

4 citations · 7 across the 5 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

GraSP: Simple yet Effective Graph Similarity Predictions

Haoran Zheng, Jieming Shi, Renchi Yang

Graph similarity computation (GSC) is to calculate the similarity between one pair of graphs, which is a fundamental problem with fruitful applications in the graph community. In G…

cs.SI2024★ 4 cited

A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation

Yiran Li, Gongyao Guo, Jieming Shi +4

Attributed networks containing entity-specific information in node attributes are ubiquitous in modeling social networks, e-commerce, bioinformatics, etc. Their inherent network to…

cs.SI2024

Effective Clustering on Large Attributed Bipartite Graphs

Renchi Yang, Yidu Wu, Xiaoyang Lin +3

Attributed bipartite graphs (ABGs) are an expressive data model for describing the interactions between two sets of heterogeneous nodes that are associated with rich attributes, su…

cs.LG2024

SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network

Ziang Zhou, Jieming Shi, Renchi Yang +2

Heterogeneous graphs are ubiquitous to model complex data. There are urgent needs on powerful heterogeneous graph neural networks to effectively support important applications. We…

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