Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GLIMG: Global and Local Item Graphs for Top-N Recommender Systems   Graph-based recommendation models work well for top-N recommender systems due
to their capability to capture the potential relationships between entities.
However, most of the existing methods only construct a single global item graph
shared by all the users and regrettably ignore the diverse tastes between
different user groups. Inspired by the success of local models for
recommendation, this paper provides the first attempt to investigate multiple
local item graphs along with a global item graph for graph-based recommendation
models. We argue that recommendation on global and local graphs outperforms
that on a single global graph or multiple local graphs. Specifically, we
propose a novel graph-based recommendation model named GLIMG (Global and Local
IteM Graphs), which simultaneously captures both the global and local user
tastes. By integrating the global and local graphs into an adapted
semi-supervised learning model, users' preferences on items are propagated
globally and locally. Extensive experimental results on real-world datasets
show that our proposed method consistently outperforms the state-of-the art
counterparts on the top-N recommendation task.

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The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
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The categories of this paper are: math-ph
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The categories of this paper are: bayes-an
2
The categories of this paper are: math