Information retrieval: recent advances and beyond

KA Hambarde, H Proenca - IEEE Access, 2023 - ieeexplore.ieee.org
This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …

GPR-OPT: A Practical Gaussian optimization criterion for implicit recommender systems

T Bai, X Wang, Z Zhang, W Song, B Wu… - Information Processing & …, 2024 - Elsevier
Implicit recommendation refers to the users' feedback on items derived from their
interactions with items, ie, clicks, and purchases. The methods in the implicit …

A holistic view on positive and negative implicit feedback for micro-video recommendation

P Gu, H Hu - Knowledge-Based Systems, 2024 - Elsevier
Micro-video online platforms have become prevalent in recent years, necessitating effective
recommender systems to help identify users' preferences. Previous works have made …

How to Forget Clients in Federated Online Learning to Rank?

S Wang, B Liu, G Zuccon - European Conference on Information Retrieval, 2024 - Springer
Data protection legislation like the European Union's General Data Protection Regulation
(GDPR) establishes the right to be forgotten: a user (client) can request contributions made …

TRAVERS: A Diversity-Based Dynamic Approach to Iterative Relevance Search over Knowledge Graphs

Z Li, Y Gu, Y Shen, W Hu, G Cheng - … of the ACM Web Conference 2023, 2023 - dl.acm.org
Relevance search over knowledge graphs seeks top-ranked answer entities that are most
relevant to a query entity. Since the semantics of relevance varies with the user need and its …

Scalable Exploration for Neural Online Learning to Rank with Perturbed Feedback

Y Jia, H Wang - Proceedings of the 45th International ACM SIGIR …, 2022 - dl.acm.org
Deep neural networks (DNNs) demonstrates significant advantages in improving ranking
performance in retrieval tasks. Driven by the recent developments in optimization and …