Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Aspect and Opinion Term Extraction for Hotel Reviews using Transfer
  Learning and Auxiliary Labels   Aspect and opinion term extraction is a critical step in Aspect-Based
Sentiment Analysis (ABSA). Our study focuses on evaluating transfer learning
using pre-trained BERT (Devlin et al., 2018) to classify tokens from hotel
reviews in bahasa Indonesia. The primary challenge is the language informality
of the review texts. By utilizing transfer learning from a multilingual model,
we achieved up to 2% difference on token level F1-score compared to the
state-of-the-art Bi-LSTM model with fewer training epochs (3 vs. 200 epochs).
The fine-tuned model clearly outperforms the Bi-LSTM model on the entity level.
Furthermore, we propose a method to include CRF with auxiliary labels as an
output layer for the BERT-based models. The CRF addition further improves the
F1-score for both token and entity level.

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The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
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The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: comp-gas