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Jianling Wang

Texas A&M University

4 papers hereh-index 171.5k citations32 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR3
  • cs.LG1
affiliations
  • Texas A&M University
Homepage
same name
  • Jianling Wang — 11 papers, h 16
  • Jianling Wang — 3 papers
  • Jianling Wang — 3 papers
  • Jianling Wang — 2 papers

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
20182022
most citedA Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists

30 citations · 30 across the 2 of their papers we have counts for

collaborators

4 papers

cs.IR2022

Learning to Augment for Casual User Recommendation

Jianling Wang, Ya Le, Bo Chang +3

Users who come to recommendation platforms are heterogeneous in activity levels. There usually exists a group of core users who visit the platform regularly and consume a large bod…

cs.LG2020

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

Kaize Ding, Jianling Wang, Jundong Li +3

Attributed networks nowadays are ubiquitous in a myriad of high-impact applications, such as social network analysis, financial fraud detection, and drug discovery. As a central an…

cs.IR2019★ 30 cited

A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists

Yun He, Jianling Wang, Wei Niu +1

User-generated item lists are a popular feature of many different platforms. Examples include lists of books on Goodreads, playlists on Spotify and YouTube, collections of images o…

cs.IR2018

Fairness-Aware Recommendation of Information Curators

Ziwei Zhu, Jianling Wang, Yin Zhang +1

This paper highlights our ongoing efforts to create effective information curator recommendation models that can be personalized for individual users, while maintaining important f…

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