Datasets:
Tasks:
Summarization
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
patent-summarization
License:
Commit
·
c2c50b0
1
Parent(s):
e0520f3
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,2 +1,406 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# Sampled big_patent Dataset
|
| 2 |
-
This is a sampled big_patent dataset containing 5000 train and 500 test rows.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
annotations_creators:
|
| 3 |
+
- no-annotation
|
| 4 |
+
language_creators:
|
| 5 |
+
- found
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
license:
|
| 9 |
+
- cc-by-4.0
|
| 10 |
+
multilinguality:
|
| 11 |
+
- monolingual
|
| 12 |
+
size_categories:
|
| 13 |
+
- 100K<n<1M
|
| 14 |
+
- 10K<n<100K
|
| 15 |
+
- 1M<n<10M
|
| 16 |
+
source_datasets:
|
| 17 |
+
- original
|
| 18 |
+
task_categories:
|
| 19 |
+
- summarization
|
| 20 |
+
task_ids: []
|
| 21 |
+
paperswithcode_id: bigpatent
|
| 22 |
+
pretty_name: Big Patent
|
| 23 |
+
tags:
|
| 24 |
+
- patent-summarization
|
| 25 |
+
dataset_info:
|
| 26 |
+
- config_name: all
|
| 27 |
+
features:
|
| 28 |
+
- name: description
|
| 29 |
+
dtype: string
|
| 30 |
+
- name: abstract
|
| 31 |
+
dtype: string
|
| 32 |
+
splits:
|
| 33 |
+
- name: train
|
| 34 |
+
num_bytes: 38367048389
|
| 35 |
+
num_examples: 1207222
|
| 36 |
+
- name: validation
|
| 37 |
+
num_bytes: 2115827002
|
| 38 |
+
num_examples: 67068
|
| 39 |
+
- name: test
|
| 40 |
+
num_bytes: 2129505280
|
| 41 |
+
num_examples: 67072
|
| 42 |
+
download_size: 10142923776
|
| 43 |
+
dataset_size: 42612380671
|
| 44 |
+
- config_name: a
|
| 45 |
+
features:
|
| 46 |
+
- name: description
|
| 47 |
+
dtype: string
|
| 48 |
+
- name: abstract
|
| 49 |
+
dtype: string
|
| 50 |
+
splits:
|
| 51 |
+
- name: train
|
| 52 |
+
num_bytes: 5683460620
|
| 53 |
+
num_examples: 174134
|
| 54 |
+
- name: validation
|
| 55 |
+
num_bytes: 313324505
|
| 56 |
+
num_examples: 9674
|
| 57 |
+
- name: test
|
| 58 |
+
num_bytes: 316633277
|
| 59 |
+
num_examples: 9675
|
| 60 |
+
download_size: 10142923776
|
| 61 |
+
dataset_size: 6313418402
|
| 62 |
+
- config_name: b
|
| 63 |
+
features:
|
| 64 |
+
- name: description
|
| 65 |
+
dtype: string
|
| 66 |
+
- name: abstract
|
| 67 |
+
dtype: string
|
| 68 |
+
splits:
|
| 69 |
+
- name: train
|
| 70 |
+
num_bytes: 4236070976
|
| 71 |
+
num_examples: 161520
|
| 72 |
+
- name: validation
|
| 73 |
+
num_bytes: 234425138
|
| 74 |
+
num_examples: 8973
|
| 75 |
+
- name: test
|
| 76 |
+
num_bytes: 231538734
|
| 77 |
+
num_examples: 8974
|
| 78 |
+
download_size: 10142923776
|
| 79 |
+
dataset_size: 4702034848
|
| 80 |
+
- config_name: c
|
| 81 |
+
features:
|
| 82 |
+
- name: description
|
| 83 |
+
dtype: string
|
| 84 |
+
- name: abstract
|
| 85 |
+
dtype: string
|
| 86 |
+
splits:
|
| 87 |
+
- name: train
|
| 88 |
+
num_bytes: 4506249306
|
| 89 |
+
num_examples: 101042
|
| 90 |
+
- name: validation
|
| 91 |
+
num_bytes: 244684775
|
| 92 |
+
num_examples: 5613
|
| 93 |
+
- name: test
|
| 94 |
+
num_bytes: 252566793
|
| 95 |
+
num_examples: 5614
|
| 96 |
+
download_size: 10142923776
|
| 97 |
+
dataset_size: 5003500874
|
| 98 |
+
- config_name: d
|
| 99 |
+
features:
|
| 100 |
+
- name: description
|
| 101 |
+
dtype: string
|
| 102 |
+
- name: abstract
|
| 103 |
+
dtype: string
|
| 104 |
+
splits:
|
| 105 |
+
- name: train
|
| 106 |
+
num_bytes: 264717412
|
| 107 |
+
num_examples: 10164
|
| 108 |
+
- name: validation
|
| 109 |
+
num_bytes: 14560482
|
| 110 |
+
num_examples: 565
|
| 111 |
+
- name: test
|
| 112 |
+
num_bytes: 14403430
|
| 113 |
+
num_examples: 565
|
| 114 |
+
download_size: 10142923776
|
| 115 |
+
dataset_size: 293681324
|
| 116 |
+
- config_name: e
|
| 117 |
+
features:
|
| 118 |
+
- name: description
|
| 119 |
+
dtype: string
|
| 120 |
+
- name: abstract
|
| 121 |
+
dtype: string
|
| 122 |
+
splits:
|
| 123 |
+
- name: train
|
| 124 |
+
num_bytes: 881101433
|
| 125 |
+
num_examples: 34443
|
| 126 |
+
- name: validation
|
| 127 |
+
num_bytes: 48646158
|
| 128 |
+
num_examples: 1914
|
| 129 |
+
- name: test
|
| 130 |
+
num_bytes: 48586429
|
| 131 |
+
num_examples: 1914
|
| 132 |
+
download_size: 10142923776
|
| 133 |
+
dataset_size: 978334020
|
| 134 |
+
- config_name: f
|
| 135 |
+
features:
|
| 136 |
+
- name: description
|
| 137 |
+
dtype: string
|
| 138 |
+
- name: abstract
|
| 139 |
+
dtype: string
|
| 140 |
+
splits:
|
| 141 |
+
- name: train
|
| 142 |
+
num_bytes: 2146383473
|
| 143 |
+
num_examples: 85568
|
| 144 |
+
- name: validation
|
| 145 |
+
num_bytes: 119632631
|
| 146 |
+
num_examples: 4754
|
| 147 |
+
- name: test
|
| 148 |
+
num_bytes: 119596303
|
| 149 |
+
num_examples: 4754
|
| 150 |
+
download_size: 10142923776
|
| 151 |
+
dataset_size: 2385612407
|
| 152 |
+
- config_name: g
|
| 153 |
+
features:
|
| 154 |
+
- name: description
|
| 155 |
+
dtype: string
|
| 156 |
+
- name: abstract
|
| 157 |
+
dtype: string
|
| 158 |
+
splits:
|
| 159 |
+
- name: train
|
| 160 |
+
num_bytes: 8877854206
|
| 161 |
+
num_examples: 258935
|
| 162 |
+
- name: validation
|
| 163 |
+
num_bytes: 492581177
|
| 164 |
+
num_examples: 14385
|
| 165 |
+
- name: test
|
| 166 |
+
num_bytes: 496324853
|
| 167 |
+
num_examples: 14386
|
| 168 |
+
download_size: 10142923776
|
| 169 |
+
dataset_size: 9866760236
|
| 170 |
+
- config_name: h
|
| 171 |
+
features:
|
| 172 |
+
- name: description
|
| 173 |
+
dtype: string
|
| 174 |
+
- name: abstract
|
| 175 |
+
dtype: string
|
| 176 |
+
splits:
|
| 177 |
+
- name: train
|
| 178 |
+
num_bytes: 8075621958
|
| 179 |
+
num_examples: 257019
|
| 180 |
+
- name: validation
|
| 181 |
+
num_bytes: 447602356
|
| 182 |
+
num_examples: 14279
|
| 183 |
+
- name: test
|
| 184 |
+
num_bytes: 445460513
|
| 185 |
+
num_examples: 14279
|
| 186 |
+
download_size: 10142923776
|
| 187 |
+
dataset_size: 8968684827
|
| 188 |
+
- config_name: y
|
| 189 |
+
features:
|
| 190 |
+
- name: description
|
| 191 |
+
dtype: string
|
| 192 |
+
- name: abstract
|
| 193 |
+
dtype: string
|
| 194 |
+
splits:
|
| 195 |
+
- name: train
|
| 196 |
+
num_bytes: 3695589005
|
| 197 |
+
num_examples: 124397
|
| 198 |
+
- name: validation
|
| 199 |
+
num_bytes: 200369780
|
| 200 |
+
num_examples: 6911
|
| 201 |
+
- name: test
|
| 202 |
+
num_bytes: 204394948
|
| 203 |
+
num_examples: 6911
|
| 204 |
+
download_size: 10142923776
|
| 205 |
+
dataset_size: 4100353733
|
| 206 |
+
config_names:
|
| 207 |
+
- a
|
| 208 |
+
- all
|
| 209 |
+
- b
|
| 210 |
+
- c
|
| 211 |
+
- d
|
| 212 |
+
- e
|
| 213 |
+
- f
|
| 214 |
+
- g
|
| 215 |
+
- h
|
| 216 |
+
- y
|
| 217 |
+
---
|
| 218 |
# Sampled big_patent Dataset
|
| 219 |
+
This is a sampled big_patent dataset containing 5000 train and 500 test rows.
|
| 220 |
+
|
| 221 |
+
The original repo card follows below.
|
| 222 |
+
|
| 223 |
+
# Dataset Card for Big Patent
|
| 224 |
+
|
| 225 |
+
## Table of Contents
|
| 226 |
+
- [Dataset Description](#dataset-description)
|
| 227 |
+
- [Dataset Summary](#dataset-summary)
|
| 228 |
+
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
|
| 229 |
+
- [Languages](#languages)
|
| 230 |
+
- [Dataset Structure](#dataset-structure)
|
| 231 |
+
- [Data Instances](#data-instances)
|
| 232 |
+
- [Data Fields](#data-fields)
|
| 233 |
+
- [Data Splits](#data-splits)
|
| 234 |
+
- [Dataset Creation](#dataset-creation)
|
| 235 |
+
- [Curation Rationale](#curation-rationale)
|
| 236 |
+
- [Source Data](#source-data)
|
| 237 |
+
- [Annotations](#annotations)
|
| 238 |
+
- [Personal and Sensitive Information](#personal-and-sensitive-information)
|
| 239 |
+
- [Considerations for Using the Data](#considerations-for-using-the-data)
|
| 240 |
+
- [Social Impact of Dataset](#social-impact-of-dataset)
|
| 241 |
+
- [Discussion of Biases](#discussion-of-biases)
|
| 242 |
+
- [Other Known Limitations](#other-known-limitations)
|
| 243 |
+
- [Additional Information](#additional-information)
|
| 244 |
+
- [Dataset Curators](#dataset-curators)
|
| 245 |
+
- [Licensing Information](#licensing-information)
|
| 246 |
+
- [Citation Information](#citation-information)
|
| 247 |
+
- [Contributions](#contributions)
|
| 248 |
+
|
| 249 |
+
## Dataset Description
|
| 250 |
+
|
| 251 |
+
- **Homepage:** [Big Patent](https://evasharma.github.io/bigpatent/)
|
| 252 |
+
- **Repository:**
|
| 253 |
+
- **Paper:** [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://arxiv.org/abs/1906.03741)
|
| 254 |
+
- **Leaderboard:**
|
| 255 |
+
- **Point of Contact:** [Lu Wang](mailto:wangluxy@umich.edu)
|
| 256 |
+
|
| 257 |
+
### Dataset Summary
|
| 258 |
+
|
| 259 |
+
BIGPATENT, consisting of 1.3 million records of U.S. patent documents along with human written abstractive summaries.
|
| 260 |
+
Each US patent application is filed under a Cooperative Patent Classification (CPC) code.
|
| 261 |
+
There are nine such classification categories:
|
| 262 |
+
- a: Human Necessities
|
| 263 |
+
- b: Performing Operations; Transporting
|
| 264 |
+
- c: Chemistry; Metallurgy
|
| 265 |
+
- d: Textiles; Paper
|
| 266 |
+
- e: Fixed Constructions
|
| 267 |
+
- f: Mechanical Engineering; Lightning; Heating; Weapons; Blasting
|
| 268 |
+
- g: Physics
|
| 269 |
+
- h: Electricity
|
| 270 |
+
- y: General tagging of new or cross-sectional technology
|
| 271 |
+
|
| 272 |
+
Current defaults are 2.1.2 version (fix update to cased raw strings) and 'all' CPC codes:
|
| 273 |
+
```python
|
| 274 |
+
from datasets import load_dataset
|
| 275 |
+
ds = load_dataset("big_patent") # default is 'all' CPC codes
|
| 276 |
+
ds = load_dataset("big_patent", "all") # the same as above
|
| 277 |
+
ds = load_dataset("big_patent", "a") # only 'a' CPC codes
|
| 278 |
+
ds = load_dataset("big_patent", codes=["a", "b"])
|
| 279 |
+
```
|
| 280 |
+
|
| 281 |
+
To use 1.0.0 version (lower cased tokenized words), pass both parameters `codes` and `version`:
|
| 282 |
+
```python
|
| 283 |
+
ds = load_dataset("big_patent", codes="all", version="1.0.0")
|
| 284 |
+
ds = load_dataset("big_patent", codes="a", version="1.0.0")
|
| 285 |
+
ds = load_dataset("big_patent", codes=["a", "b"], version="1.0.0")
|
| 286 |
+
```
|
| 287 |
+
|
| 288 |
+
|
| 289 |
+
### Supported Tasks and Leaderboards
|
| 290 |
+
|
| 291 |
+
[More Information Needed]
|
| 292 |
+
|
| 293 |
+
### Languages
|
| 294 |
+
|
| 295 |
+
English
|
| 296 |
+
|
| 297 |
+
## Dataset Structure
|
| 298 |
+
|
| 299 |
+
### Data Instances
|
| 300 |
+
|
| 301 |
+
Each instance contains a pair of `description` and `abstract`. `description` is extracted from the Description section of the Patent while `abstract` is extracted from the Abstract section.
|
| 302 |
+
```
|
| 303 |
+
{
|
| 304 |
+
'description': 'FIELD OF THE INVENTION \n [0001] This invention relates to novel calcium phosphate-coated implantable medical devices and processes of making same. The unique calcium-phosphate coated implantable medical devices minimize...',
|
| 305 |
+
'abstract': 'This invention relates to novel calcium phosphate-coated implantable medical devices...'
|
| 306 |
+
}
|
| 307 |
+
```
|
| 308 |
+
|
| 309 |
+
### Data Fields
|
| 310 |
+
|
| 311 |
+
- `description`: detailed description of patent.
|
| 312 |
+
- `abstract`: Patent abastract.
|
| 313 |
+
|
| 314 |
+
### Data Splits
|
| 315 |
+
|
| 316 |
+
| | train | validation | test |
|
| 317 |
+
|:----|------------------:|-------------:|-------:|
|
| 318 |
+
| all | 1207222 | 67068 | 67072 |
|
| 319 |
+
| a | 174134 | 9674 | 9675 |
|
| 320 |
+
| b | 161520 | 8973 | 8974 |
|
| 321 |
+
| c | 101042 | 5613 | 5614 |
|
| 322 |
+
| d | 10164 | 565 | 565 |
|
| 323 |
+
| e | 34443 | 1914 | 1914 |
|
| 324 |
+
| f | 85568 | 4754 | 4754 |
|
| 325 |
+
| g | 258935 | 14385 | 14386 |
|
| 326 |
+
| h | 257019 | 14279 | 14279 |
|
| 327 |
+
| y | 124397 | 6911 | 6911 |
|
| 328 |
+
|
| 329 |
+
## Dataset Creation
|
| 330 |
+
|
| 331 |
+
### Curation Rationale
|
| 332 |
+
|
| 333 |
+
[More Information Needed]
|
| 334 |
+
|
| 335 |
+
### Source Data
|
| 336 |
+
|
| 337 |
+
#### Initial Data Collection and Normalization
|
| 338 |
+
|
| 339 |
+
[More Information Needed]
|
| 340 |
+
|
| 341 |
+
#### Who are the source language producers?
|
| 342 |
+
|
| 343 |
+
[More Information Needed]
|
| 344 |
+
|
| 345 |
+
### Annotations
|
| 346 |
+
|
| 347 |
+
#### Annotation process
|
| 348 |
+
|
| 349 |
+
[More Information Needed]
|
| 350 |
+
|
| 351 |
+
#### Who are the annotators?
|
| 352 |
+
|
| 353 |
+
[More Information Needed]
|
| 354 |
+
|
| 355 |
+
### Personal and Sensitive Information
|
| 356 |
+
|
| 357 |
+
[More Information Needed]
|
| 358 |
+
|
| 359 |
+
## Considerations for Using the Data
|
| 360 |
+
|
| 361 |
+
### Social Impact of Dataset
|
| 362 |
+
|
| 363 |
+
[More Information Needed]
|
| 364 |
+
|
| 365 |
+
### Discussion of Biases
|
| 366 |
+
|
| 367 |
+
[More Information Needed]
|
| 368 |
+
|
| 369 |
+
### Other Known Limitations
|
| 370 |
+
|
| 371 |
+
[More Information Needed]
|
| 372 |
+
|
| 373 |
+
## Additional Information
|
| 374 |
+
|
| 375 |
+
### Dataset Curators
|
| 376 |
+
|
| 377 |
+
[More Information Needed]
|
| 378 |
+
|
| 379 |
+
### Licensing Information
|
| 380 |
+
|
| 381 |
+
[More Information Needed]
|
| 382 |
+
|
| 383 |
+
### Citation Information
|
| 384 |
+
|
| 385 |
+
```bibtex
|
| 386 |
+
@article{DBLP:journals/corr/abs-1906-03741,
|
| 387 |
+
author = {Eva Sharma and
|
| 388 |
+
Chen Li and
|
| 389 |
+
Lu Wang},
|
| 390 |
+
title = {{BIGPATENT:} {A} Large-Scale Dataset for Abstractive and Coherent
|
| 391 |
+
Summarization},
|
| 392 |
+
journal = {CoRR},
|
| 393 |
+
volume = {abs/1906.03741},
|
| 394 |
+
year = {2019},
|
| 395 |
+
url = {http://arxiv.org/abs/1906.03741},
|
| 396 |
+
eprinttype = {arXiv},
|
| 397 |
+
eprint = {1906.03741},
|
| 398 |
+
timestamp = {Wed, 26 Jun 2019 07:14:58 +0200},
|
| 399 |
+
biburl = {https://dblp.org/rec/journals/corr/abs-1906-03741.bib},
|
| 400 |
+
bibsource = {dblp computer science bibliography, https://dblp.org}
|
| 401 |
+
}
|
| 402 |
+
```
|
| 403 |
+
|
| 404 |
+
### Contributions
|
| 405 |
+
|
| 406 |
+
Thanks to [@mattbui](https://github.com/mattbui) for adding this dataset.
|