The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xe9 in position 1992: invalid continuation byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 506, in __iter__
yield from self.ex_iterable
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 398, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/text/text.py", line 98, in _generate_tables
batch = f.read(self.config.chunksize)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
out = read(*args, **kwargs)
File "<frozen codecs>", line 325, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe9 in position 1992: invalid continuation byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
This dataset contains check-ins in NYC and Tokyo collected for about 10 month (from 12 April 2012 to 16 February 2013). It contains 227,428 check-ins in New York city and 573,703 check-ins in Tokyo. Each check-in is associated with its time stamp, its GPS coordinates and its semantic meaning (represented by fine-grained venue-categories). This dataset was originally used to study the spatial-temporal regularity of user activity in LBSNs.
Please download the dataset here and check the readme file here.
Please cite our paper if you publish material based on those datasets.
Dingqi Yang, Daqing Zhang, Vincent W. Zheng, Zhiyong Yu. Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs. IEEE Trans. on Systems, Man, and Cybernetics: Systems, (TSMC), 45(1), 129-142, 2015. [PDF]
This dataset includes long-term (about 10 months) check-in data in New York city and Tokyo collected from Foursquare from 12 April 2012 to 16 February 2013. It contains two files in tsv format. Each file contains 8 columns, which are:
- User ID (anonymized)
- Venue ID (Foursquare)
- Venue category ID (Foursquare)
- Venue category name (Fousquare)
- Latitude
- Longitude
- Timezone offset in minutes (The offset in minutes between when this check-in occurred and the same time in UTC)
- UTC time
The file dataset_TSMC2014_NYC.txt contains 227428 check-ins in New York city. The file dataset_TSMC2014_TKY.txt contains 537703 check-ins in Tokyo.
============================================================================================================================= Please cite our paper if you publish material based on this dataset.
============================================================================================================================= REFERENCES
@article{yang2014modeling, author={Yang, Dingqi and Zhang, Daqing and Zheng, Vincent. W. and Yu, Zhiyong}, journal={IEEE Transactions on Systems, Man, and Cybernetics: Systems}, title={Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs}, year={2015}, volume={45}, number={1}, pages={129--142}, ISSN={2168-2216}, publisher={IEEE} }
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