Litcius/Paper detail

Challenges and research opportunities in eCommerce search and recommendations

Manos Tsagkias, Tracy Holloway King, Surya Kallumadi, Vanessa Murdock, Maarten de Rijke

2020ACM SIGIR Forum105 citationsDOIOpen Access PDF

Abstract

With the rapid adoption of online shopping, academic research in the eCommerce domain has gained traction. However, significant research challenges remain, spanning from classic eCommerce search problems such as matching textual queries to multi-modal documents and ranking optimization for two-sided marketplaces to human-computer interaction and recommender systems for discovery and browsing. These research areas are important for understanding customer behavior, driving engagement, and improving product discoverability and conversion. In this article we identify the challenges and highlight research opportunities to improve the eCommerce customer experience.

Topics & Concepts

DiscoverabilityComputer scienceRecommender systemRanking (information retrieval)Domain (mathematical analysis)Matching (statistics)Customer engagementWorld Wide WebProduct (mathematics)Data scienceInformation retrievalSocial mediaStatisticsMathematical analysisMathematicsGeometryInformation Retrieval and Search BehaviorAdvanced Text Analysis TechniquesRecommender Systems and Techniques