In this work, we propose a novel attention-based item collaborative filtering model(AICF) which adopts three different attention mechanisms to estimate the weights of historical items that users have interacted with. Compared with the state-of-the-art recommendation models, the AICF model with ...
论文 Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention 介绍了基于领域知识的注意力机制如何用于推荐系统的。其中的 Attention Model 框架和上一节中介绍的 Hierarchical Attention Model 十分类似，唯一的不同就是它的输入使用了其他领域信息。不同于传统的 CF 推荐模...
Concatenation-based Attention Attentive Collaborative Filtering: Multimedia Recommendation with Item- and ...
There are mainly two categories of traditional rec- ommendation algorithms: Content-Based (CB) and Collaborative Filtering (CF). CF methods make recommendations mainly accord- ing to the historical feedback information. They usually perform better when there is sufficient feedback information but ...
Example 1:Attentive Collaborative Filtering Multimedia Recommendation with Item- and Component-Level Attention_sigir17 Example 3:Dipole Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Network_2017KDD Example 5:Learning to Generate Rock Descriptions from Multivariate Well Log...
2.2 Concatenation-based Attention 具体我们来举几个例子,可能具体实现上,有略微区别,不过都大同小异: Example 1:Attentive Collaborative Filtering Multimedia Recommendation with Item- and Component-Level Attention_sigir17 Example 3:Dipole Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurre...
1) 2017年发表在ACM SIGIR会议上的题为“Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention”[10]的文章,介绍了基于领域知识的注意力机制如何用于推荐系统的。其中的注意力模型框架类似于层级注意力模型,唯一的不同就是它的输入使用了其他领域信息。文章中的注意力模...
METHOD AND APPARATUS FOR RECOMMENDING IMAGE BASED ON USER PROFILE USING FEATURE-BASED COLLABORATIVE FILTERING TO RESOLVE NEW ITEM RECOMMENDATION Provided are a method and apparatus for recommending an image based on a user profile using feature-based collaborative filtering. To generate the user pro...
2.2 Concatenation-based Attention 具体我们来举几个例子,可能具体实现上,有略微区别,不过都大同小异: Example 1:Attentive Collaborative Filtering Multimedia Recommendation with Item- and Component-Level Attention_sigir17 Example 3:Dipole Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurre...
[1] Chen, Jingyuan, et al. "Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention." In SIGIR, 2017. idea: there exists item- and component-level implicitness which blurs the underlying users' preferences in multimedia recommendation ...