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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 |
|---|---|---|
842,298,552 |
9b7015a7-73a2-4ce0-94ff-309f27d1f5fb
|
495ef092-0399-4fcf-a6d1-7b4f52b7de04
|
1,596,437,394 |
826320b2-f123-42f7-b5b9-6df66895f959
|
312f1bc9-fdd9-4f3c-ac9e-5821919eebf7
|
-1,257,837,707 |
34b17750-7827-45f7-a797-42b92f427a8f
|
80f94a05-de92-49fb-b259-dd1c34bcf442
|
760,669,881 |
51153c31-19d4-4d93-807d-c0a55ff3eb91
|
3821d21d-d973-4b36-bc03-1b986c67759c
|
-1,914,121,319 |
9741bdd6-91cf-4ed5-9f6b-761222eb5533
|
5e43d83e-8e68-4b33-a43b-794db3272e72
|
-1,159,078,222 |
ad3c08ad-1313-4df5-9ff4-2580a3a7b716
|
1d014985-6ecf-44d4-b3fe-2a9232b7b54c
|
-298,765,330 |
0926d786-138b-414f-998e-b1ae5a69511b
|
76ce65ed-0fdd-499f-9028-1d60abd28e78
|
639,512,652 |
5b6bb1a8-a2da-472b-af85-f5b9e4255282
|
e003e14c-1573-4db5-aaef-6502ade7733d
|
1,743,191,055 |
ae587998-065c-4307-9ab7-05995db8d364
|
d31f2c43-8ad0-4600-87f0-63ad45d8197f
|
-650,058,398 |
da0d5321-804a-4f7d-9e7d-a25b8f449edb
|
eb97d45f-701d-4979-845f-a626a43a0c06
|
-2,005,618,708 |
5bca7ed3-f6a9-4d2a-8ca6-b21c691c9bf5
|
557bc43e-8765-4264-910c-09d85b2ee016
|
1,770,111,340 |
5b1befc0-e8fb-450b-970c-28b7e8c2069b
|
60a29a0d-c393-41c9-935b-d3f4fcc98f3e
|
-2,123,217,228 |
62e677b8-6d13-4044-a01b-6aefa6cfac94
|
271e0ced-8022-4111-981c-06c298870d31
|
-57,400,887 |
39b4d5ee-9c15-45f9-8ab4-f68d67aa13f0
|
aa565f0d-14d7-4375-8156-6c78f606068b
|
-526,013,592 |
3c565a65-8e2b-4a09-b1c8-2ba9f77ebb78
|
eec3d065-ee9c-4c2c-b746-52b9f4f1fafd
|
-1,910,296,631 |
25edb845-b48a-4d86-976d-39be64834504
|
1ae4b2fd-347b-4621-a5fe-f1f18460bb90
|
-1,880,139,766 |
bfc7d671-0ca0-437d-9cb5-1d8c2c1a41ad
|
dde2ddee-a832-4f77-b0aa-db60760d7db0
|
-1,300,865,214 |
b8c07907-297a-4619-9bc2-6fb9ac0f8fac
|
d7b36e45-4b88-4fa0-98c4-26b4bf58a4a5
|
1,401,228,916 |
3a1d124b-daa9-4ac6-8115-db48f5edf2b5
|
06f35290-31fe-47bf-b72a-a53111ca0997
|
160,682,111 |
ea9ab997-4ca3-482f-8b8f-056c4ceafd4c
|
add045c7-7713-42f5-be56-39425f1eb51a
|
354,972,897 |
9e2d2ab7-7977-45cf-be19-76e18fa9bffa
|
c9deaf58-fcfa-413c-98de-50ce184645c7
|
1,286,201,902 |
05b4f802-31bb-4a7c-86ef-06204177afb1
|
cbe5c1c7-8d24-4a24-b03e-f9faa8ec2aaa
|
2,131,474,732 |
8c17f57b-752e-421e-a651-f2690d85df7f
|
6d254913-93be-4c41-8506-4eedf68cdffb
|
1,570,935,802 |
7d08688f-0db4-4861-b175-078100b9ebd5
|
690252bb-12eb-4190-bdcd-cf98f7105974
|
-1,786,649,723 |
527a2619-a9a6-4a85-8382-c7330c9875ac
|
48da54c5-228f-40c6-a8f1-c939db15b160
|
-1,344,970,131 |
f58dd297-8507-49a1-a7c0-3a1bc1b86d13
|
5da465e1-46dc-4e85-a1ac-ec4ed3d554b9
|
-565,530,733 |
c05ecbd6-0cca-4c68-936b-9de0bcab7bcb
|
148c91d7-36a4-498d-bea1-a8ef21d98385
|
594,471,075 |
c1a3c2a6-8ca6-4360-8cde-09134e18869c
|
ce23f038-e2c6-4dbe-9e4e-aa503699834f
|
215,285,681 |
d781efcf-fd6f-485a-9a2b-5a9af4835a01
|
78ea5cf3-42f2-4bf0-9c8b-758f21782195
|
1,588,350,157 |
6a1fd487-4362-4f78-84c4-6f26a5f44a80
|
d80e18b0-cc80-4ef4-a004-eddcc2d3e204
|
1,482,461,278 |
c65da3a9-61dc-45cd-814b-cf28852f3c09
|
10409f83-2f74-48dc-addb-a2b36d4a195e
|
-1,354,044,772 |
14daf391-62ba-4b24-aa7e-4963b091bd24
|
fcf77c8d-332a-4be8-8b9c-325cea80d46b
|
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75b5120c-bf75-4446-be49-03d1a42b62b9
|
e77a436a-d9c3-4338-a8a9-152a94e9c5a0
|
-1,536,909,841 |
3a729277-688c-43e2-9e72-2e05a61f2c00
|
a79ea880-fe6b-4f9e-8381-6e002a0505cf
|
-466,997,400 |
66c2fed2-2fbb-418d-8533-e2b81d104f16
|
d6d507f3-0dbd-4c47-a6f6-4b84e375e079
|
1,842,056,846 |
c8849dbb-1d4e-4367-8894-4ecea56e5d6d
|
c4b443f1-8d47-485a-8a55-d18615226080
|
-573,353,656 |
61e12f51-3ed8-449a-88b8-6122825dc368
|
86cd03ab-d241-4518-8f33-7a7104e2edc4
|
-1,333,477,874 |
9a18e84e-e55e-404c-9f08-d01cbcdedf67
|
b3e3993e-820e-4f5b-adfe-6f260dad92f1
|
108,113,176 |
dfdad541-3d12-42be-a33c-8c0c4fcfc739
|
d745f31b-8b06-40f1-a8da-88d1de444460
|
267,406,881 |
4ac5ea24-0fa7-49e7-9781-a020f466a5f1
|
beb68de4-17d8-4e42-8ebd-ed88bf9d51cc
|
176,299,139 |
389334c1-4eff-4ab4-8cc6-64513cffb939
|
6ad01f45-51d5-4af4-9a79-fec20916a5b7
|
-2,067,816,368 |
386a13ec-9abf-464d-a5ae-435b9f134cdc
|
9ac12c56-cd3d-44b3-8542-c05016c056c6
|
-1,822,769,822 |
7c411e23-fbdd-4776-b1c9-c3a416b09cce
|
b0bc7a7e-c471-4b75-a7f1-54ecb7cf3498
|
1,290,956,262 |
c1263d37-c88c-402c-b2cb-fea9792f7401
|
08506a24-0aeb-49dd-9367-1707ca6c4bfe
|
1,572,518,821 |
dcf5d204-fa0c-4e35-b5de-b5c01ab824ce
|
f84451d4-78fa-4829-9820-b828caa53b6c
|
-1,609,584,023 |
0ecf4220-5036-42d7-84cf-32e119bbfd45
|
f8d25ba2-3cfc-40dd-94bc-02f01b1d0b2d
|
2,084,310,515 |
a32b113f-152f-445c-bbf6-af722f966d96
|
b49e666e-6aca-42d2-9b42-1e92186e5141
|
903,829,953 |
8bba37c0-4303-4dda-9fe6-25171c28c8c1
|
94f2196f-ddb8-46f6-8a88-7377acd243f3
|
-1,344,821,242 |
fc29e001-19b8-4397-8195-20bcffb59030
|
0dfec7de-d2c2-48e7-aa6c-7f47f12857a5
|
1,179,247,747 |
0a8430d4-f6d8-428e-a4da-2fe460243858
|
ccd97e1e-c3f5-429f-8032-c36b529541d7
|
-1,574,393,857 |
229e745a-c225-4b5e-b86c-2568caed719b
|
48727652-4dbd-463a-8c8c-702d18e652f2
|
-1,429,975,449 |
553dbad3-ffcb-4cad-ad11-6436e5d93b11
|
01ee6a66-3ee9-4109-9671-4892f0912663
|
-259,766,667 |
148e4a61-c7a7-445b-b5c4-8f1519c756ee
|
36c2946b-57fc-45dc-b8cf-b43bd174a002
|
-292,638,733 |
34a6cf2f-a9b4-4dd8-88fc-921a7329f4ed
|
a599c8e4-baa7-415c-8989-256ffc600875
|
-1,201,631,833 |
75b673ef-b974-4dd8-bba0-c5af795f6c46
|
53f331c4-0f90-477b-b701-02957b171a73
|
-1,718,214,209 |
98e9ea49-4734-40e2-8b49-83216b81383b
|
e8d930bc-2947-4a50-8e4b-4376545aa6aa
|
-1,238,746,323 |
71b1c703-c347-4cc7-bff3-fa5e743b3057
|
177f77f0-3249-436f-8568-1d68aca720c5
|
1,186,430,576 |
a34ba7bf-7d13-43ce-8a68-4ee3cfd093c6
|
9ea03d0f-d902-40e8-adef-d32074e08995
|
857,797,267 |
1a801c37-92ec-4b77-b509-772197985920
|
3954363e-f045-4204-92fa-231c59eac0dc
|
1,110,759,460 |
cc18eba3-a78a-4622-94ae-85a183b2062a
|
8f6be9ad-6cbf-4616-ba26-4ca87f06470e
|
299,150,943 |
d24a91ad-23b1-478b-9da4-c7f764e6374e
|
53ad2278-5bc0-4f2d-8063-6f9c1fc74c44
|
577,860,068 |
d15173aa-0886-4dcd-b67a-eb94251e801a
|
bb31ac24-17d3-4adf-b5b9-12b36d08324e
|
-1,859,457,855 |
9867bc6a-f051-49bc-bf9e-a65d215201f8
|
db216811-1a23-4458-b822-a6937b7d96c7
|
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e2025757-5396-44cf-9fc2-16b1f0817421
|
104f7a5c-1194-4eb4-ba11-a09ce95d5631
|
1,076,217,634 |
7de528ab-fe36-4cd8-a635-7283adbdcd4d
|
9feb7b1f-a840-4788-953b-5a7c8241ed42
|
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30bc2321-0ec6-48eb-86c4-342a18c81b07
|
75ba2600-c8f7-42fa-8147-23a17e152682
|
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be7a3435-0d21-4960-b9c0-349d738e24e5
|
ec1dd5b2-c4f7-467c-9698-bd8573b6ddf1
|
499,730,129 |
9914fd21-becc-4e10-b67f-656a9323ecaa
|
325ee6da-3912-4e17-97e3-67477322ba01
|
1,829,415,926 |
f512ad8d-5e9e-4766-97bd-87fdae27286b
|
1092a4b9-cef7-4c18-a962-91df4db1db0a
|
-1,275,401,570 |
2b5e7a9a-93f7-4613-a5c8-4147b3d4405c
|
b83233f4-99c9-4e0d-a728-3a298cee68ee
|
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cdbc53c0-d097-4d38-a3ae-51a24b6f987d
|
a4c2a664-f958-47ac-987e-ccbb71f0b150
|
1,035,003,406 |
09b4bc62-79d5-4d26-b646-73f25d52dc78
|
205a1b3c-30a4-4e5c-a3d0-02242f240dbf
|
417,895,080 |
53d2ef28-c04f-41ba-8c7b-24d1fee22590
|
ced3c969-04b5-4035-bba1-2309f217cd2f
|
488,510,420 |
c92247c7-ed2d-4440-9652-7c9a65727dbe
|
4b5e0604-3920-4174-bd65-6336c5e740fb
|
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0750ce21-371e-40d0-839d-742a85df6d98
|
934a8bb5-2a8d-48cc-bc77-a704edafc8a0
|
591,459,209 |
e84661f3-a79d-4352-b461-e2bc2c11e1c1
|
cdeb145d-19e1-4d5e-ac57-646278029877
|
591,341,294 |
b1904c84-cf27-4e5d-9917-47859dd805d6
|
27bb3f03-2f8f-4702-b0fe-8c54ccb18713
|
2,029,203,998 |
0b34d3d7-a2bb-4b5f-bf57-b39f0d7af340
|
0c14a677-4ec4-4587-9b1e-860474038fa8
|
1,499,411,603 |
3b9fe270-e53f-4206-a7b3-a175d5be0799
|
4ce621b9-cd34-4e06-8ee1-ae194431bfcf
|
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0a2686d9-84e4-4244-beed-8f636c96a18c
|
4b9ccbb2-cf7b-4a5e-820c-94c2d3b2e4f3
|
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d971ae65-75d1-4661-b761-563836494dc2
|
b1b820d9-79db-497a-914c-b483e246a1e8
|
1,384,676,389 |
1d6f68b1-0e67-4c6c-b236-82fc2c1fb001
|
3019efe3-d157-40c8-918b-60a408db49c2
|
840,669,862 |
7d51ba0f-a2c4-4637-a99d-7b3065d554ff
|
f0093412-7eea-4ed6-b423-9b431eb82895
|
1,860,318,030 |
a783b374-6dd3-4e1d-b6cc-e7e6600f6f60
|
c68e6817-7809-4cd0-9a1d-62b1ea4e32b7
|
1,351,681,432 |
474416e1-ed83-4b03-8535-9d3e51d37756
|
dc0933f2-3198-4e86-b1a4-d415ffbe6be1
|
2,041,622,331 |
6e45e3a2-2e95-4400-9743-5248a6a21b7c
|
e916ef6a-7b8d-4718-af7e-fbc7675e4392
|
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e098f28a-2563-4b72-93b9-3539f2876dd0
|
fc58326b-a23f-421a-97c9-15709762963c
|
2,087,575,977 |
3b0a0dd7-2514-4173-9f29-0ae1a3d3fc7d
|
4a8cd7d1-ed2b-472e-b000-1a45ce62a1ee
|
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437a32f8-2997-4c25-9b83-b1121fcc784e
|
7f33ec3b-e138-4a2d-b65c-f9662d7aa187
|
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569b75c6-54f9-4988-96ba-b85e73563c78
|
42286dca-dcd2-4d8c-9492-26a65463dce5
|
709,127,278 |
4d524521-3d78-450a-bf7d-9dd307bb9ee4
|
3c37837f-9a91-447c-b1ac-f365c5ac4d2b
|
170,983,351 |
21ce17dc-ae0b-4fff-aadf-6009b2d358d6
|
7293f487-95b4-4e06-81ee-022dd93742d5
|
1,659,947,058 |
ab7d8740-9162-4b17-95fd-7be53e85f417
|
c1f1b91a-be12-403b-9432-fca15d059f6c
|
629,480,361 |
e0bb6bb1-2752-4eee-abbd-a78187446770
|
f546999c-d7f2-4acb-9753-19ddb1857558
|
-1,437,552,600 |
0453c8e7-560f-4422-bf7b-967abcd2e40e
|
0b4cb693-465b-4e4c-8dd5-293dbeb1753c
|
635,038,974 |
0f2e0980-ff10-42c0-b343-f423b3117b90
|
04ec683c-ac13-4cf9-b887-c5c53c1c7fd3
|
-207,515,806 |
365dc941-a4c6-45f4-890e-74621a3b3e7d
|
05407d44-501d-426f-973d-8d7cb4d877c9
|
-21,796,264 |
f79f5def-8d67-4e7c-b875-31bb6a67ae4a
|
2511f4db-3ed1-4337-bda0-153cdfd39446
|
-325,296,404 |
0b6f0b2a-65a1-489f-b6e9-c9f192a2aa07
|
4bb2fe5a-da87-4abd-afa6-b33b6f53ab96
|
2,889,363 |
9c251362-aa5c-4ecb-a9a5-86e1c400c633
|
3e6333fc-19b3-4d41-93cb-e087196c58b4
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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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