User response prediction in online advertising
Z Gharibshah, X Zhu - aCM Computing Surveys (CSUR), 2021 - dl.acm.org
Online advertising, as a vast market, has gained significant attention in various platforms
ranging from search engines, third-party websites, social media, and mobile apps. The …
ranging from search engines, third-party websites, social media, and mobile apps. The …
Denoising and prompt-tuning for multi-behavior recommendation
In practical recommendation scenarios, users often interact with items under multi-typed
behaviors (eg, click, add-to-cart, and purchase). Traditional collaborative filtering techniques …
behaviors (eg, click, add-to-cart, and purchase). Traditional collaborative filtering techniques …
Multi-level sequence denoising with cross-signal contrastive learning for sequential recommendation
Sequential recommender systems (SRSs) aim to suggest next item for a user based on her
historical interaction sequences. Recently, many research efforts have been devoted to …
historical interaction sequences. Recently, many research efforts have been devoted to …
Hierarchical item inconsistency signal learning for sequence denoising in sequential recommendation
Sequential recommender systems aim to recommend the next items in which target users
are most interested based on their historical interaction sequences. In practice, historical …
are most interested based on their historical interaction sequences. In practice, historical …
Evolution of the online sales of sustainable products in the COVID-19 pandemic
In the context of the COVID-19 pandemic, online sales have increased in recent years for
many products. Responsible consumption has also been considered by households and …
many products. Responsible consumption has also been considered by households and …
AI-Driven Contextual Advertising: Toward Relevant Messaging Without Personal Data
E Häglund, J Björklund - Journal of Current Issues & Research in …, 2024 - Taylor & Francis
In programmatic advertising, bids are increasingly based on knowledge of the surrounding
media context. This shift toward contextual advertising is in part a counter-reaction to the …
media context. This shift toward contextual advertising is in part a counter-reaction to the …
Tutorial on online user engagement: Metrics and optimization
User engagement plays a central role in companies operating online services, such as
search engines, news portals, e-commerce sites, entertainment services, and social …
search engines, news portals, e-commerce sites, entertainment services, and social …
Deriving user-and content-specific rewards for contextual bandits
Bandit algorithms have gained increased attention in recommender systems, as they
provide effective and scalable recommendations. These algorithms use reward functions …
provide effective and scalable recommendations. These algorithms use reward functions …
(m) ad to see me? intelligent advertisement placement: Balancing user annoyance and advertising effectiveness
Advertising is an unavoidable albeit a frustrating part of mobile interactions. Due to limited
form factor, mobile advertisements often resort to intrusive strategies where they temporarily …
form factor, mobile advertisements often resort to intrusive strategies where they temporarily …
Improving bounce rate prediction for rare queries by leveraging landing page signals
Y Dolma, R Kalani, A Agrawal, S Basu - Companion Proceedings of the …, 2021 - dl.acm.org
Bounce rate prediction for clicked ads in sponsored search advertising is crucial for
improving the quality of ads shown to the user. Bounce rate represents the proportion of …
improving the quality of ads shown to the user. Bounce rate represents the proportion of …