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In this paper, we explore effective fusion of user-item ratings and item attributes to improve recommendations, we propose an attribute-aware deep attentive recommendation model, which embeds attribute information into the latent semantic space of items through the attention mechanism, forming more accurate item ...
Nov 9, 2020
Since the rich semantics of attribute information has become a great supplement to the ratings data in designing recommender systems, fusing attributes ...
Abstract: Since the rich semantics of attribute information has become a great supplement to the ratings data in designing recommender systems, ...
In this paper, we explore effective fusion of movie ratings and plot texts, we propose a deep plot-aware generalized matrix factorization for collaborative ...
Mar 20, 2020 · To address this problem, in this paper, we present an attribute-aware attentive graph convolution network (A2-GCN). In particular, we first ...
Oct 1, 2024 · For our clients, Attentive's advanced personalized recommendation system offers significant value. By leveraging rich user and item attributes, ...
In this paper, we propose a novel Attribute-aware Neural Attentive Model (ANAM) to address these problems. ANAM adopts an attention mechanism to explicitly ...
An attribute-aware attentive graph convolution network capable of incorporating associate attributes to strengthen the user and item representation learning ...
Jul 8, 2018 · ABSTRACT. Next basket recommendation is a new type of recommen- dation, which recommends a set of items, or a basket, to the user.
Apr 4, 2022 · In this paper, we address these limitations by proposing a context and attribute- aware recommender model (CARCA) that can capture the dynamic.