Learning to Hash for Recommendation: A Survey
F Luo, H Zhang, T Li, J Wu - arXiv preprint arXiv:2412.03875, 2024 - arxiv.org
With the explosive growth of users and items, Recommender Systems (RS) are facing
unprecedented challenges on both retrieval efficiency and storage cost. Fortunately …
unprecedented challenges on both retrieval efficiency and storage cost. Fortunately …
Unsupervised multi-index semantic hashing
Semantic hashing represents documents as compact binary vectors (hash codes) and
allows both efficient and effective similarity search in large-scale information retrieval. The …
allows both efficient and effective similarity search in large-scale information retrieval. The …
[PDF][PDF] Discrete Listwise Personalized Ranking for Fast Top-N Recommendation with Implicit Feedback.
We address the efficiency problem of personalized ranking from implicit feedback by
hashing users and items with binary codes, so that top-N recommendation can be fast …
hashing users and items with binary codes, so that top-N recommendation can be fast …
Discrete Listwise Content-aware Recommendation
To perform online inference efficiently, hashing techniques, devoted to encoding model
parameters as binary codes, play a key role in reducing the computational cost of content …
parameters as binary codes, play a key role in reducing the computational cost of content …
Graph-Based Recommendation for Sparse and Heterogeneous User Interactions
SB Bruun, KK Leśniak, M Biasini, V Carmignani… - … on Information Retrieval, 2023 - Springer
Recommender system research has oftentimes focused on approaches that operate on
large-scale datasets containing millions of user interactions. However, many small …
large-scale datasets containing millions of user interactions. However, many small …
Learning similarity preserving binary codes for recommender systems
Hashing-based Recommender Systems (RSs) are widely studied to provide scalable
services. The existing methods for the systems combine three modules to achieve efficiency …
services. The existing methods for the systems combine three modules to achieve efficiency …
[图书][B] Discrete Techniques for Efficient Recommendations
Y Zhang - 2022 - search.proquest.com
Recommender systems have been extensively applied in various big data scenarios with
the rapid development of online platforms. However, big data brings three challenges for …
the rapid development of online platforms. However, big data brings three challenges for …
Representation Learning for Efficient and Effective Similarity Search and Recommendation
C Hansen - arXiv preprint arXiv:2109.01815, 2021 - arxiv.org
How data is represented and operationalized is critical for building computational solutions
that are both effective and efficient. A common approach is to represent data objects as …
that are both effective and efficient. A common approach is to represent data objects as …