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Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To maximize relevance, we leverage two complementary objectives: behavioral relevance (results users…

Information Retrieval · Computer Science 2026-03-10 Evangelia Christakopoulou , Vivekkumar Patel , Hemanth Velaga , Sandip Gaikwad , Sean Suchter , Venkat Sundaranatha

We consider the revenue maximization problem for an online retailer who plans to display in order a set of products differing in their prices and qualities. Consumers have attention spans, i.e., the maximum number of products they are…

Machine Learning · Computer Science 2025-11-11 Ningyuan Chen , Anran Li , Shuoguang Yang

Sponsored search is an indispensable business model and a major revenue contributor of almost all the search engines. From the advertisers' side, participating in ranking the search results by paying for the sponsored search advertisement…

Information Retrieval · Computer Science 2018-03-28 Li He , Liang Wang , Kaipeng Liu , Bo Wu , Weinan Zhang

Personalized search has been a hot research topic for many years and has been widely used in e-commerce. This paper describes our solution to tackle the challenge of personalized e-commerce search at CIKM Cup 2016. The goal of this…

Information Retrieval · Computer Science 2017-08-16 Chen Wu , Ming Yan , Luo Si

In web search, mutual influences between documents have been studied from the perspective of search result diversification. But the methods in web search is not directly applicable to e-commerce search because of their differences. And…

Information Retrieval · Computer Science 2019-03-28 Tao Zhuang , Wenwu Ou , Zhirong Wang

The search engine plays a fundamental role in online e-commerce systems, to help users find the products they want from the massive product collections. Relevance is an essential requirement for e-commerce search, since showing products…

Information Retrieval · Computer Science 2021-02-16 Shaowei Yao , Jiwei Tan , Xi Chen , Keping Yang , Rong Xiao , Hongbo Deng , Xiaojun Wan

The Web 2.0 paradigm has radically changed the way businesses are run all around the world. Moreover, e-Commerce has overcome in daily shopping activities. For management teams, the assessment, evaluation, and forecasting of online incomes…

Computers and Society · Computer Science 2017-01-09 Ilija S. Hristoski , Pece J. Mitrevski

E-commerce queries are often short and ambiguous. Consequently, query understanding often uses query rewriting to disambiguate user-input queries. While using e-commerce search tools, users tend to enter multiple searches, which we call…

Information Retrieval · Computer Science 2022-09-27 Simiao Zuo , Qingyu Yin , Haoming Jiang , Shaohui Xi , Bing Yin , Chao Zhang , Tuo Zhao

In this paper, we address the problem of evaluating whether results served by an e-commerce search engine for a query are good or not. This is a critical question in evaluating any e-commerce search engine. While this question is…

Information Retrieval · Computer Science 2018-08-02 Rohan Kumar , Mohit Kumar , Neil Shah , Christos Faloutsos

Online marketplaces frequently run pricing experiments in environments where users choose from a list of items. In these settings, items compete for users' limited attention and demand, creating interference among items within a list:…

Econometrics · Economics 2026-03-17 Mahyar Habibi , Zahra Khanalizadeh , Negar Ziaeian

Accurate query-product relevance labeling is indispensable to generate ground truth dataset for search ranking in e-commerce. Traditional approaches for annotating query-product pairs rely on human-based labeling services, which is…

Information Retrieval · Computer Science 2025-02-27 Jayant Sachdev , Sean D Rosario , Abhijeet Phatak , He Wen , Swati Kirti , Chittaranjan Tripathy

Result relevance scoring is critical to e-commerce search user experience. Traditional information retrieval methods focus on keyword matching and hand-crafted or counting-based numeric features, with limited understanding of item semantic…

Information Retrieval · Computer Science 2021-04-27 Yunjiang Jiang , Yue Shang , Rui Li , Wen-Yun Yang , Guoyu Tang , Chaoyi Ma , Yun Xiao , Eric Zhao

How might we design Reinforcement Learning (RL)-based recommenders that encourage aligning user trajectories with the underlying user satisfaction? Three research questions are key: (1) measuring user satisfaction, (2) combatting sparsity…

Sponsored product advertisements constitute a major revenue source for online marketplaces such as Amazon, Walmart, and Alibaba. A key operational challenge in these systems lies in the Sponsored Listings Ranking (SLR) problem, that is,…

General Economics · Economics 2025-11-13 Haihao Lu , Luyang Zhang , Yuting Zhu

In this paper we address the explainability of web search engines. We propose two explainable elements on the search engine result page: a visualization of query term weights and a visualization of passage relevance. The idea is that search…

Information Retrieval · Computer Science 2021-06-10 Ioannis Chios , Suzan Verberne

We consider the problem of personalization of online services from the viewpoint of ad targeting, where we seek to find the best ad categories to be shown to each user, resulting in improved user experience and increased advertisers'…

Artificial Intelligence · Computer Science 2016-06-30 Nemanja Djuric , Mihajlo Grbovic , Vladan Radosavljevic , Narayan Bhamidipati , Slobodan Vucetic

In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue. However, most of the state-of-the-art auction…

Computer Science and Game Theory · Computer Science 2021-01-11 Zhilin Zhang , Xiangyu Liu , Zhenzhe Zheng , Chenrui Zhang , Miao Xu , Junwei Pan , Chuan Yu , Fan Wu , Jian Xu , Kun Gai

Generative retrieval introduces a groundbreaking paradigm to document retrieval by directly generating the identifier of a pertinent document in response to a specific query. This paradigm has demonstrated considerable benefits and…

Information Retrieval · Computer Science 2024-10-28 Mingming Li , Huimu Wang , Zuxu Chen , Guangtao Nie , Yiming Qiu , Guoyu Tang , Lin Liu , Jingwei Zhuo

Over the past years, e-commerce platforms have expanded substantially, providing customers with convenient shopping experiences. To enhance e-commerce websites, it's essential to grasp user engagement and factors affecting conversion rates.…

Social and Information Networks · Computer Science 2024-03-26 Amrutha Muralidhar , Yathindra Lakkanna

Customer behavioral data significantly impacts e-commerce search systems. However, in the case of less common queries, the associated behavioral data tends to be sparse and noisy, offering inadequate support to the search mechanism. To…

Information Retrieval · Computer Science 2024-10-03 Ziqi Zhang , Yupin Huang , Quan Deng , Jinghui Xiao , Vivek Mittal , Jingyuan Deng