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Wei Ju

47 papers hereh-index 322.6k citations104 works total

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

author position
  • first author12
  • middle author31
  • last author2

Across the 45 of 47 papers where every author was matched, so the position is known.

fields
  • cs.LG30
  • cs.CL6
  • cs.IR6
  • cs.CV3
  • cs.AI1
  • cs.MM1
same name
  • Wei Ju — 7 papers, h 2
  • Wei Ju — 4 papers, h 3
  • Wei Ju — 2 papers, h 0
  • Wei Ju — 1 paper, h 1
  • Wei Ju — 1 paper, h 2

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
20202026
most citedA Comprehensive Survey on Deep Graph Representation Learning

337 citations · 823 across the 46 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 1 cited

Kernel-based Substructure Exploration for Next POI Recommendation

Wei Ju, Yifang Qin, Ziyue Qiao +4

Point-of-Interest (POI) recommendation, which benefits from the proliferation of GPS-enabled devices and location-based social networks (LBSNs), plays an increasingly important rol…

cs.IR2022★ 89 cited

DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation

Yifang Qin, Yifan Wang, Fang Sun +6

Point-of-Interest (POI) recommendation plays a vital role in various location-aware services. It has been observed that POI recommendation is driven by both sequential and geograph…

cs.LG2022

GLCC: A General Framework for Graph-Level Clustering

Wei Ju, Yiyang Gu, Binqi Chen +5

This paper studies the problem of graph-level clustering, which is a novel yet challenging task. This problem is critical in a variety of real-world applications such as protein cl…

cs.LG2022★ 33 cited

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

Wei Ju, Junwei Yang, Meng Qu +3

This paper studies semi-supervised graph classification, which is an important problem with various applications in social network analysis and bioinformatics. This problem is typi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.