Temporal Event Sequences
Collection
A collection of real-world temporal event sequences from multiple domains.
•
6 items
•
Updated
•
1
dim_process
int64 25
25
| seq_idx
int64 0
2.67k
| seq_len
int64 37
100
| time_since_start
sequencelengths 37
100
| time_since_last_event
sequencelengths 37
100
| type_event
sequencelengths 37
100
| type_text
sequencelengths 37
100
|
|---|---|---|---|---|---|---|
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"Nice Answer",
"Enlightened",
"Nice Answer",
"Nice Answer",
"Enlightened",
"Nice Answer",
"Nice Answer",
"Nice Answer",
"Enlightened",
"Nice Answer",
"Enlightened",
"Notable Question",
"Nice Answer",
"Nice Answer",
"Enlightened",
"Nice Answer",
"Guru",
"Yearling",
"Nice Answer",
"Notable Question",
"Nice Answer",
"Nice Answer",
"Nice Answer",
"Enlightened",
"Nice Answer",
"Enlightened"
] |
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Stack Overflow Dataset
This dataset contains badge awards earned by users on Stack Overflow between January 1, 2022, and December 31, 2023. It includes 3,336 sequences with 187,836 events and 25 badge types, derived from the Stack Exchange Data Dump under the CC BY-SA 4.0 license. The detailed data preprocessing steps used to create this dataset can be found in the TPP-LLM paper and TPP-LLM-Embedding paper.
If you find this dataset useful, we kindly invite you to cite the following papers:
@article{liu2024tppllmm,
title={TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models},
author={Liu, Zefang and Quan, Yinzhu},
journal={arXiv preprint arXiv:2410.02062},
year={2024}
}
@article{liu2024efficient,
title={Efficient Retrieval of Temporal Event Sequences from Textual Descriptions},
author={Liu, Zefang and Quan, Yinzhu},
journal={arXiv preprint arXiv:2410.14043},
year={2024}
}
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