Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Modeling Inter-Aspect Dependencies with a Non-temporal Mechanism for
  Aspect-Based Sentiment Analysis   For multiple aspects scenario of aspect-based sentiment analysis (ABSA),
existing approaches typically ignore inter-aspect relations or rely on temporal
dependencies to process aspect-aware representations of all aspects in a
sentence. Although multiple aspects of a sentence appear in a non-adjacent
sequential order, they are not in a strict temporal relationship as natural
language sequence, thus the aspect-aware sentence representations should not be
treated as temporal dependency processing. In this paper, we propose a novel
non-temporal mechanism to enhance the ABSA task through modeling inter-aspect
dependencies. Furthermore, we focus on the well-known class imbalance issue on
the ABSA task and address it by down-weighting the loss assigned to
well-classified instances. Experiments on two distinct domains of SemEval 2014
task 4 demonstrate the effectiveness of our proposed approach.

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The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
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The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol