On Sampled Metrics for Item Recommendation 论文链接:dl.acm.org/doi/abs/10.1 accepted by KDD2020 1. 研究目标 由于在个性化推荐中物品(item)的数量十分之大,且在数据集中,对于每一位用户而言,未交互的数据量十分大,无法得知哪些物品是用户不喜欢的,大多数得到的是用户喜欢的物品,因
On Sampled Metrics for Item Recommendation 论文链接:https://dl.acm.org/doi/abs/10.1145/3394486.3403226 accepted by KDD2020 1. 研究目标 由于在个性化推荐中物品(item)的数量十分之大,且在数据集中,对于每一位用户而言,未交互的数据量十分大,无法得知哪些物品是用户不喜欢的,大多数得... ...
2021Fast and Memory-Efficient Tucker Decomposition for Answering Diverse Time Range Queries 2020On Sampled Metrics for Item Recommendation 2019Optimizing Impression Counts for Outdoor Advertising 2018Adversarial Attacks on Neural Networks for Graph Data ...
论文题目: On Sampled Metrics for Item Recommendation 论文地址: https://dl.acm.org/doi/abs/10.1145/3394486.3403226 论文发表于: KDD 2020 best paper(CCF A类会议) 论文大体内容: 本文主要论述了在推荐领域中,使用采样testset进行evaluate来比较各个模型,有可能会得出...【...
该论文对抽样指标进行了更详细的调查,结果表明它们与确切指标的性能不一致。另外,实验结果表明抽样规模越小,指标之间的差异就越小,而且对于非常小的抽样规模,所有指标都会塌陷为AUC指标。所以该论文提出了一种改进的抽样评价指标来提高评价质量。 二、主要评价指标...
Cross-domain recommendation aims to integrate data from multiple domains and introduce information from source domains, thereby achieving good recommendati
(This article belongs to the Special Issue: Generative AI for Recommendation Services) Abstract Artificial Intelligence (AI) is fundamentally transforming medical diagnostics, driving advancements that enhance accuracy, efficiency, and personalized patient care. This narrative review explores AI integration ...
We built a researcher identifier management system called the Researcher Name Resolver (RNR) to assist with the name disambiguation of authors in digital l
item images; presenting recommendations of the identified items according to a rank order based on degrees of similarity between the query image and each item image among the set of item images; and re-ranking the recommendations in response to a detected selection of a recommendation from among ...
image among a set of item images, the presenting being performed by a processor of a machine, the presenting being performed by at least one processor of a machine; and re-ranking the recommendations in response to a detected selection of a recommendation from among the recommendations presented...