Search Results for author: Jianling Wang

Found 10 papers, 6 papers with code

Session-based Recommendation with Hypergraph Attention Networks

no code implementations28 Dec 2021 Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee

Session-based recommender systems aim to improve recommendations in short-term sessions that can be found across many platforms.

Session-Based Recommendations

Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

1 code implementation18 Dec 2021 Kaize Ding, Jianling Wang, James Caverlee, Huan Liu

Inspired by the extensive success of deep learning, graph neural networks (GNNs) have been proposed to learn expressive node representations and demonstrated promising performance in various graph learning tasks.

Graph Learning Meta-Learning

Exploring Heterogeneous Metadata for Video Recommendation with Two-tower Model

no code implementations22 Sep 2021 Jianling Wang, Ainur Yessenalina, Alireza Roshan-Ghias

Online video services acquire new content on a daily basis to increase engagement, and improve the user experience.

Recommendation Systems

Sequential Recommendation for Cold-start Users with Meta Transitional Learning

1 code implementation13 Jul 2021 Jianling Wang, Kaize Ding, James Caverlee

A fundamental challenge for sequential recommenders is to capture the sequential patterns of users toward modeling how users transit among items.

Few-Shot Learning Sequential Recommendation +1

Weakly-supervised Graph Meta-learning for Few-shot Node Classification

no code implementations12 Jun 2021 Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu

Graphs are widely used to model the relational structure of data, and the research of graph machine learning (ML) has a wide spectrum of applications ranging from drug design in molecular graphs to friendship recommendation in social networks.

Classification Graph Learning +3

Fairness-aware Personalized Ranking Recommendation via Adversarial Learning

1 code implementation14 Mar 2021 Ziwei Zhu, Jianling Wang, James Caverlee

This is paper is an extended and reorganized version of our SIGIR 2020~\cite{zhu2020measuring} paper.

Fairness Frame +1

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

1 code implementation23 Jun 2020 Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu

By constructing a pool of semi-supervised node classification tasks to mimic the real test environment, GPN is able to perform \textit{meta-learning} on an attributed network and derive a highly generalizable model for handling the target classification task.

Classification Drug Discovery +5

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

1 code implementation30 Dec 2019 Yun He, Jianling Wang, Wei Niu, James Caverlee

User-generated item lists are a popular feature of many different platforms.

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