126 citations · 425 across the 18 of their papers we have counts for
7 papers · 1 filter
GraphHINGE: Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network
Jiarui Jin, Kounianhua Du, Weinan Zhang +5
Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations. Recent attempts either rely on explicit path rea…
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph
Jiarui Jin, Jiarui Qin, Yuchen Fang +5
There is an influx of heterogeneous information network (HIN) based recommender systems in recent years since HIN is capable of characterizing complex graphs and contains rich sema…
User Behavior Retrieval for Click-Through Rate Prediction
Jiarui Qin, Weinan Zhang, Xin Wu +3
Click-through rate (CTR) prediction plays a key role in modern online personalization services. In practice, it is necessary to capture user's drifting interests by modeling sequen…
A Deep Recurrent Survival Model for Unbiased Ranking
Jiarui Jin, Yuchen Fang, Weinan Zhang +7
Position bias is a critical problem in information retrieval when dealing with implicit yet biased user feedback data. Unbiased ranking methods typically rely on causality models a…
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
Jiarui Qin, Kan Ren, Yuchen Fang +2
Sequential recommendation task aims to predict user preference over items in the future given user historical behaviors. The order of user behaviors implies that there are resource…
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
Kan Ren, Jiarui Qin, Yuchen Fang +8
User response prediction, which models the user preference w.r.t. the presented items, plays a key role in online services. With two-decade rapid development, nowadays the cumulate…
Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising
Kan Ren, Yuchen Fang, Weinan Zhang +5
In online advertising, the Internet users may be exposed to a sequence of different ad campaigns, i.e., display ads, search, or referrals from multiple channels, before led up to a…