A Comprehensive Survey on Retrieval Methods in Recommender Systems
In an era dominated by information overload, effective recommender systems are essential
for managing the deluge of data across digital platforms. Multi-stage cascade ranking …
for managing the deluge of data across digital platforms. Multi-stage cascade ranking …
Contrastive cross-domain recommendation in matching
Cross-domain recommendation (CDR) aims to provide better recommendation results in the
target domain with the help of the source domain, which is widely used and explored in real …
target domain with the help of the source domain, which is widely used and explored in real …
Constructing tree-based index for efficient and effective dense retrieval
Recent studies have shown that Dense Retrieval (DR) techniques can significantly improve
the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the …
the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the …
On missing labels, long-tails and propensities in extreme multi-label classification
The propensity model introduced by Jain et al has become a standard approach for dealing
with missing and long-tail labels in extreme multi-label classification (XMLC). In this paper …
with missing and long-tail labels in extreme multi-label classification (XMLC). In this paper …
A survey on incremental update for neural recommender systems
P Zhang, S Kim - arxiv preprint arxiv:2303.02851, 2023 - arxiv.org
Recommender Systems (RS) aim to provide personalized suggestions of items for users
against consumer over-choice. Although extensive research has been conducted to address …
against consumer over-choice. Although extensive research has been conducted to address …
Equi-vocal: Synthesizing queries for compositional video events from limited user interactions
We introduce EQUI-VOCAL: a new system that automatically synthesizes queries over
videos from limited user interactions. The user only provides a handful of positive and …
videos from limited user interactions. The user only provides a handful of positive and …
Improving accuracy and diversity in matching of recommendation with diversified preference network
Real-world recommendation systems need to deal with millions of item candidates.
Therefore, most practical large-scale recommendation systems usually contain two modules …
Therefore, most practical large-scale recommendation systems usually contain two modules …
Adaptive domain interest network for multi-domain recommendation
Industrial recommender systems usually hold data from multiple business scenarios and are
expected to provide recommendation services for these scenarios simultaneously. In the …
expected to provide recommendation services for these scenarios simultaneously. In the …
Joint learning of deep retrieval model and product quantization based embedding index
Embedding index that enables fast approximate nearest neighbor (ANN) search, serves as
an indispensable component for state-of-the-art deep retrieval systems. Traditional …
an indispensable component for state-of-the-art deep retrieval systems. Traditional …
Generalized test utilities for long-tail performance in extreme multi-label classification
Extreme multi-label classification (XMLC) is a task of selecting a small subset of relevant
labels from a very large set of possible labels. As such, it is characterized by long-tail labels …
labels from a very large set of possible labels. As such, it is characterized by long-tail labels …