3.7k citations · 6.9k across the 74 of their papers we have counts for
15 papers · 1 filter
A Graph-Enhanced Click Model for Web Search
Jianghao Lin, Weiwen Liu, Xinyi Dai +6
To better exploit search logs and model users' behavior patterns, numerous click models are proposed to extract users' implicit interaction feedback. Most traditional click models…
Retrieval & Interaction Machine for Tabular Data Prediction
Jiarui Qin, Weinan Zhang, Rong Su +5
Prediction over tabular data is an essential task in many data science applications such as recommender systems, online advertising, medical treatment, etc. Tabular data is structu…
An Adversarial Imitation Click Model for Information Retrieval
Xinyi Dai, Jianghao Lin, Weinan Zhang +7
Modern information retrieval systems, including web search, ads placement, and recommender systems, typically rely on learning from user feedback. Click models, which study how use…
U-rank: Utility-oriented Learning to Rank with Implicit Feedback
Xinyi Dai, Jiawei Hou, Qing Liu +6
Learning to rank with implicit feedback is one of the most important tasks in many real-world information systems where the objective is some specific utility, e.g., clicks and rev…
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…
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
Sijin Zhou, Xinyi Dai, Haokun Chen +5
Interactive recommender system (IRS) has drawn huge attention because of its flexible recommendation strategy and the consideration of optimal long-term user experiences. To deal w…
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…
Deep Landscape Forecasting for Real-time Bidding Advertising
Kan Ren, Jiarui Qin, Lei Zheng +3
The emergence of real-time auction in online advertising has drawn huge attention of modeling the market competition, i.e., bid landscape forecasting. The problem is formulated as…
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…
QA4IE: A Question Answering based Framework for Information Extraction
Lin Qiu, Hao Zhou, Yanru Qu +7
Information Extraction (IE) refers to automatically extracting structured relation tuples from unstructured texts. Common IE solutions, including Relation Extraction (RE) and open…
Collaborative Filtering with Graph-based Implicit Feedback
Minzhe Niu, Weinan Zhang, Yanru Qu +4
Introducing consumed items as users' implicit feedback in matrix factorization (MF) method, SVD++ is one of the most effective collaborative filtering methods for personalized reco…
Learning the Gain Values and Discount Factors of DCG
Ke Zhou, Hongyuan Zha, Gui-Rong Xue +1
Evaluation metrics are an essential part of a ranking system, and in the past many evaluation metrics have been proposed in information retrieval and Web search. Discounted Cumulat…