Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Many-to-one Recurrent Neural Network for Session-based Recommendation   This paper presents the D2KLab team's approach to the RecSys Challenge 2019
which focuses on the task of recommending accommodations based on user
sessions. What is the feeling of a person who says "Rooms of the hotel are
enormous, staff are friendly and efficient"? It is positive. Similarly to the
sequence of words in a sentence where one can affirm what the feeling is,
analysing a sequence of actions performed by a user in a website can lead to
predict what will be the item the user will add to his basket at the end of the
shopping session. We propose to use a many-to-one recurrent neural network that
learns the probability that a user will click on an accommodation based on the
sequence of actions he has performed during his browsing session. More
specifically, we combine a rule-based algorithm with a Gated Recurrent Unit RNN
in order to sort the list of accommodations that is shown to the user. We
optimized the RNN on a validation set, tuning the hyper-parameters such as the
learning rate, the batch-size and the accommodation embedding size. This
analogy with the sentiment analysis task gives promising results. However, it
is computationally demanding in the training phase and it needs to be further
tuned.

29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ