Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Item Recommendation Approach by Fusing Images based on Neural
  Networks   There are rich formats of information in the network, such as rating, text,
image, and so on, which represent different aspects of user preferences. In the
field of recommendation, how to use those data effectively has become a
difficult subject. With the rapid development of neural network, researching on
multi-modal method for recommendation has become one of the major directions.
In the existing recommender systems, numerical rating, item description and
review are main information to be considered by researchers. However, the
characteristics of the item may affect the user's preferences, which are rarely
used for recommendation models. In this work, we propose a novel model to
incorporate visual factors into predictors of people's preferences, namely
MF-VMLP, based on the recent developments of neural collaborative filtering
(NCF). Firstly, we get visual presentation via a pre-trained convolutional
neural network (CNN) model. To obtain the nonlinearities interaction of latent
vectors and visual vectors, we propose to leverage a multi-layer perceptron
(MLP) to learn. Moreover, the combination of MF and MLP has achieved
collaborative filtering recommendation between users and items. Our experiments
conduct Amazon's public dataset for experimental validation and
root-mean-square error (RMSE) as evaluation metrics. To some extent,
experimental result on a real-world data set demonstrates that our model can
boost the recommendation performance.

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The categories of this paper are: q-fin
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The categories of this paper are: chao-dyn
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ex
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The categories of this paper are: econ
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The categories of this paper are: funct-an
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The categories of this paper are: atom-ph
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The categories of this paper are: q-bio
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
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The categories of this paper are: hep-lat
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The categories of this paper are: stat