Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Latent Structure Mining with Contrastive Modality Fusion for Multimedia
  Recommendation   Recent years have witnessed growing interests in multimedia recommendation,
which aims to predict whether a user will interact with an item with multimodal
contents. Previous studies focus on modeling user-item interactions with
multimodal features included as side information. However, this scheme is not
well-designed for multimedia recommendation. Firstly, only collaborative
item-item relationships are implicitly modeled through high-order
item-user-item co-occurrences. We argue that the latent semantic item-item
structures underlying these multimodal contents could be beneficial for
learning better item representations and assist the recommender models to
comprehensively discover candidate items. Secondly, previous studies disregard
the fine-grained multimodal fusion. Although having access to multiple
modalities might allow us to capture rich information, we argue that the simple
coarse-grained fusion by linear combination or concatenation in previous work
is insufficient to fully understand content information and item
relationships.To this end, we propose a latent structure MIning with
ContRastive mOdality fusion method (MICRO for brevity). To be specific, we
devise a novel modality-aware structure learning module, which learns item-item
relationships for each modality. Based on the learned modality-aware latent
item relationships, we perform graph convolutions that explicitly inject item
affinities to modality-aware item representations. Then, we design a novel
contrastive method to fuse multimodal features. These enriched item
representations can be plugged into existing collaborative filtering methods to
make more accurate recommendations. Extensive experiments on real-world
datasets demonstrate the superiority of our method over state-of-the-art
baselines.

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The categories of this paper are: math-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
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The categories of this paper are: physics
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The categories of this paper are: supr-con
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The categories of this paper are: q-bio
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
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The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: cmp-lg