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20192022
most citedFi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

234 citations · 450 across the 14 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 7 cited

GraphFM: Graph Factorization Machines for Feature Interaction Modeling

Shu Wu, Zekun Li, Yunyue Su +3

Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand…

cs.IR2021★ 2 cited

Represent Items by Items: An Enhanced Representation of the Target Item for Recommendation

Yinjiang Cai, Zeyu Cui, Shu Wu +2

Item-based collaborative filtering (ICF) has been widely used in industrial applications such as recommender system and online advertising. It models users' preference on target it…

cs.LG2021★ 10 cited

DyGCN: Dynamic Graph Embedding with Graph Convolutional Network

Zeyu Cui, Zekun Li, Shu Wu +4

Graph embedding, aiming to learn low-dimensional representations (aka. embeddings) of nodes, has received significant attention recently. Recent years have witnessed a surge of eff…

cs.IR2021★ 15 cited

Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval

Xueli Yu, Weizhi Xu, Zeyu Cui +2

The ad-hoc retrieval task is to rank related documents given a query and a document collection. A series of deep learning based approaches have been proposed to solve such problem…

cs.IR2021★ 2 cited

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

Yufeng Zhang, Jinghao Zhang, Zeyu Cui +2

To retrieve more relevant, appropriate and useful documents given a query, finding clues about that query through the text is crucial. Recent deep learning models regard the task a…