Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MARS: Memory Attention-Aware Recommender System   In this paper, we study the problem of modeling users' diverse interests.
Previous methods usually learn a fixed user representation, which has a limited
ability to represent distinct interests of a user. In order to model users'
various interests, we propose a Memory Attention-aware Recommender System
(MARS). MARS utilizes a memory component and a novel attentional mechanism to
learn deep \textit{adaptive user representations}. Trained in an end-to-end
fashion, MARS adaptively summarizes users' interests. In the experiments, MARS
outperforms seven state-of-the-art methods on three real-world datasets in
terms of recall and mean average precision. We also demonstrate that MARS has a
great interpretability to explain its recommendation results, which is
important in many recommendation scenarios.

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The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
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The categories of this paper are: atom-ph
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The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
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The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math