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Existing advertisements click-through rate (CTR) prediction models are mainly dependent on behavior ID features, which are learned based on the historical user-ad interactions. Nevertheless, behavior ID features relying on historical user…

Information Retrieval · Computer Science 2022-09-26 Tan Yu , Zhipeng Jin , Jie Liu , Yi Yang , Hongliang Fei , Ping Li

With the rise of online e-commerce platforms, more and more customers prefer to shop online. To sell more products, online platforms introduce various modules to recommend items with different properties such as huge discounts. A web page…

Machine Learning · Computer Science 2020-09-01 Xu He , Bo An , Yanghua Li , Haikai Chen , Rundong Wang , Xinrun Wang , Runsheng Yu , Xin Li , Zhirong Wang

It can be observed that the purchasing decision of an individual consumer in an electronic marketplace is determined by a set of factors, such as personal characteristics of the consumer, product pricing, minimum price-quantity combination…

Computer Science and Game Theory · Computer Science 2024-06-27 Dipankar Das

We consider an online matching problem with concave returns. This problem is a significant generalization of the Adwords allocation problem and has vast applications in online advertising. In this problem, a sequence of items arrive…

Data Structures and Algorithms · Computer Science 2015-06-09 Xiao Alison Chen , Zizhuo Wang

It has become increasingly clear that recommender systems that overly focus on short-term engagement prevents users from exploring diverse interests, ultimately hurting long-term user experience. To tackle this challenge, numerous…

Information Retrieval · Computer Science 2025-01-13 Yuyan Wang , Cheenar Banerjee , Samer Chucri , Fabio Soldo , Sriraj Badam , Ed H. Chi , Minmin Chen

Today's online platforms heavily lean on algorithmic recommendations for bolstering user engagement and driving revenue. However, these recommendations can impact multiple stakeholders simultaneously -- the platform, items (sellers), and…

Information Retrieval · Computer Science 2024-05-28 Qinyi Chen , Jason Cheuk Nam Liang , Negin Golrezaei , Djallel Bouneffouf

The development of information technology and Internet has led to rapidly progressed in e-commerce and online shopping, due to the convenience that they provide consumers. E-commerce and online shopping are still not able to fully replace…

Computers and Society · Computer Science 2015-12-09 Nahla Khalil

We tackle the problem of understanding visual ads where given an ad image, our goal is to rank appropriate human generated statements describing the purpose of the ad. This problem is generally addressed by jointly embedding images and…

Computer Vision and Pattern Recognition · Computer Science 2018-07-05 Karuna Ahuja , Karan Sikka , Anirban Roy , Ajay Divakaran

In fashion e-commerce platforms, product discovery is one of the key components of a good user experience. There are numerous ways using which people find the products they desire. Similar product recommendations is one of the popular modes…

Information Retrieval · Computer Science 2018-07-02 Pankaj Agarwal , Sreekanth Vempati , Sumit Borar

A retailer is purchasing goods in bundles from suppliers and then selling these goods in bundles to customers; her goal is to maximize profit, which is the revenue obtained from selling goods minus the cost of purchasing those goods. In…

Data Structures and Algorithms · Computer Science 2025-08-01 Yossi Azar , Niv Buchbinder , Roie Levin , Or Vardi

This paper addresses the challenge of improving user experience on e-commerce platforms by enhancing product ranking relevant to users' search queries. Ambiguity and complexity of user queries often lead to a mismatch between the user's…

Information Retrieval · Computer Science 2024-10-22 Hadeel Saadany , Swapnil Bhosale , Samarth Agrawal , Diptesh Kanojia , Constantin Orasan , Zhe Wu

Standard ad auction formats do not immediately extend to settings where multiple size configurations and layouts are available to advertisers. In these settings, the sale of web advertising space increasingly resembles a combinatorial…

Computer Science and Game Theory · Computer Science 2020-11-10 Rad Niazadeh , Jason Hartline , Nicole Immorlica , Mohammad Reza Khani , Brendan Lucier

In online advertising (Ad), advertisers are always eager to know how to globally optimize their budget allocation strategies across different channels for more conversions such as orders, payments, etc. Ignoring competition among different…

Computer Science and Game Theory · Computer Science 2023-05-12 Guangyuan Shen , Shenjie Sun , Dehong Gao , Shaolei Li , Libin Yang , Yongping Shi , Wei Ning

We analyze the effect of sponsored data platforms when Internet service providers (ISPs) compete for subscribers and content providers (CPs) compete for a share of the bandwidth usage by the customers. Our analytical model is of a full…

Networking and Internet Architecture · Computer Science 2019-06-04 Pooja Vyavahare , D. Manjunath , Jayakrishnan Nair

Recommender systems are an essential component of e-commerce marketplaces, helping consumers navigate massive amounts of inventory and find what they need or love. In this paper, we present an approach for generating personalized item…

Information Retrieval · Computer Science 2021-02-12 Tian Wang , Yuri M. Brovman , Sriganesh Madhvanath

One of the main challenges in recommender systems is data sparsity which leads to high variance. Several attempts have been made to improve the bias-variance trade-off using auxiliary information. In particular, document modeling-based…

Information Retrieval · Computer Science 2021-09-14 Meysam Varasteh , Mehdi Soleiman Nejad , Hadi Moradi , Mohammad Amin Sadeghi , Ahmad Kalhor

This paper develops a theoretical model to study the economic incentives for a social media platform to moderate user-generated content. We show that a self-interested platform can use content moderation as an effective marketing tool to…

General Economics · Economics 2023-04-20 Yi Liu , Pinar Yildirim , Z. John Zhang

Content feeds provided by platforms such as X (formerly Twitter) and TikTok are consumed by users on a daily basis. In this paper, we revisit the native advertising problem in content feeds, initiated by Ieong et al. Given a sequence of…

Data Structures and Algorithms · Computer Science 2025-02-05 Guangyi Zhang , Ilie Sarpe , Aristides Gionis

E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). Keyphrases must be pertinent to items; otherwise, it can result in seller dissatisfaction and poor…

Information Retrieval · Computer Science 2025-05-28 Soumik Dey , Wei Zhang , Hansi Wu , Bingfeng Dong , Binbin Li

The E-commerce advertising platforms typically sell commercial traffic through either second-price auction (SPA) or first-price auction (FPA). SPA was historically prevalent due to its dominant strategy incentive-compatible (DSIC) for…

Computer Science and Game Theory · Computer Science 2025-10-20 Qi Li , Wendong Huang , Qichen Ye , Wutong Xu , Cheems Wang , Rongquan Bai , Wei Yuan , Guan Wang , Chuan Yu , Jian Xu
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