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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 5 new columns ({'review_positive', 'review_score', 'review_negative', 'review_title', 'review_helpful_votes'}) and 1 missing columns ({'user_id'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Booking-com/accommodation-reviews/rectour24/train_reviews.csv (at revision 7292684aee2d49e33f68d1f2bc74e4488b091dce)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              review_id: string
              accommodation_id: int64
              review_title: string
              review_positive: string
              review_negative: string
              review_score: double
              review_helpful_votes: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1156
              to
              {'accommodation_id': Value(dtype='int64', id=None), 'review_id': Value(dtype='string', id=None), 'user_id': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 5 new columns ({'review_positive', 'review_score', 'review_negative', 'review_title', 'review_helpful_votes'}) and 1 missing columns ({'user_id'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Booking-com/accommodation-reviews/rectour24/train_reviews.csv (at revision 7292684aee2d49e33f68d1f2bc74e4488b091dce)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

accommodation_id
int64
review_id
string
user_id
string
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End of preview.
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Booking.com Accommodation Review Dataset

This repository contains the training set of the user-generated review dataset of Booking.com reviews. The training set contains about 1.6M reviews from 40k accommodations around the world. All reviews were written by guests who stayed at the accommodation.

The dataset consists of English reviews published in 2023. All reviews have passed a moderation process ensuring they are genuine and do not violate the platform guidelines. In order to preserve user privacy, no personally identifiable information was included in the data. Similarly, to protect business-sensitive statistics, the dataset is limited to only tens of thousands accommodations. Finally, we selected only informative reviews that include at least 3 topics based on the Text2topic model.

The following table describes the fields in the dataset:

Column Description
review_title The title of the review
review_positive Positive ("liked") section in review.
review_negative Negative ("disliked") section in review.
guest_score Review score for the stay
review_helpful_votes How many users marked the review as helpful
guest_type There are 4 types of traveller types: Solo traveller (1 adult) /
Couple (2 adults) / Group (>2 adults) / Family with
children (adults & children)
guest_country Anonymized country from which the reservation was made
room_nights The length of the reservation, i.e. number of nights booked
month The month of the check-in date of the reservation
accommodation_id An anonymized accommodation ID
accommodation_type The type of the accommodation, e.g. hotel, apartment, hostel
accommodation_score The overall average guest review score for the accommodation
accommodation_country Country of the accommodation
accommodation_star_rating Accommodation star rating is provided by the property, and is
usually determined by an official accommodation rating
organisation or another third party
location_is_beach Is the accommodation located in a beach location
location_is_ski Is the accommodation located in a ski location
location_is_city_center Is the accommodation located in the city center

License

The dataset is published under the following non-commercial license

Citation

Paper on arXiv

@misc{igebaria2024enhancingtraveldecisionmakingcontrastive,
      title={Enhancing Travel Decision-Making: A Contrastive Learning Approach for Personalized Review Rankings in Accommodations}, 
      author={Reda Igebaria and Eran Fainman and Sarai Mizrachi and Moran Beladev and Fengjun Wang},
      year={2024},
      eprint={2407.00787},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2407.00787}, 
}
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