Datasets:
web_of_science

Languages:

English

Tags:

Dataset card Viewer Files Files and versions Community

web_of_science / web_of_science.py

system HF staff

Update files from the datasets library (from 1.0.0)

1ec3c61 over 2 years ago

raw history blame

No virus

5.11 kB

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	# Lint as: python3
	"""Web of science"""

	from __future__ import absolute_import, division, print_function

	import os

	import datasets


	_CITATION = """\
	@inproceedings{kowsari2017HDLTex,
	title={HDLTex: Hierarchical Deep Learning for Text Classification},
	author={Kowsari, Kamran and Brown, Donald E and Heidarysafa, Mojtaba and Jafari Meimandi, Kiana and and Gerber, Matthew S and Barnes, Laura E},
	booktitle={Machine Learning and Applications (ICMLA), 2017 16th IEEE International Conference on},
	year={2017},
	organization={IEEE}
	}
	"""

	_DESCRIPTION = """\
	The Web Of Science (WOS) dataset is a collection of data of published papers
	available from the Web of Science. WOS has been released in three versions: WOS-46985, WOS-11967 and WOS-5736. WOS-46985 is the
	full dataset. WOS-11967 and WOS-5736 are two subsets of WOS-46985.

	"""

	_DATA_URL = (
	"https://data.mendeley.com/datasets/9rw3vkcfy4/6/files/c9ea673d-5542-44c0-ab7b-f1311f7d61df/WebOfScience.zip?dl=1"
	)


	class WebOfScienceConfig(datasets.BuilderConfig):
	"""BuilderConfig for WebOfScience."""

	def __init__(self, **kwargs):
	"""BuilderConfig for WebOfScience.

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(WebOfScienceConfig, self).__init__(version=datasets.Version("6.0.0", ""), **kwargs)


	class WebOfScience(datasets.GeneratorBasedBuilder):
	"""Web of Science"""

	BUILDER_CONFIGS = [
	WebOfScienceConfig(
	name="WOS5736",
	description="""Web of Science Dataset WOS-5736: This dataset contains 5,736 documents with 11 categories which include 3 parents categories.""",
	),
	WebOfScienceConfig(
	name="WOS11967",
	description="""Web of Science Dataset WOS-11967: This dataset contains 11,967 documents with 35 categories which include 7 parents categories.""",
	),
	WebOfScienceConfig(
	name="WOS46985",
	description="""Web of Science Dataset WOS-46985: This dataset contains 46,985 documents with 134 categories which include 7 parents categories.""",
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION + self.config.description,
	features=datasets.Features(
	{
	"input_data": datasets.Value("string"),
	"label": datasets.Value("int32"),
	"label_level_1": datasets.Value("int32"),
	"label_level_2": datasets.Value("int32"),
	}
	),
	# No default supervised_keys (as we have to pass both premise
	# and hypothesis as input).
	supervised_keys=None,
	homepage="https://data.mendeley.com/datasets/9rw3vkcfy4/6",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	# dl_manager is a datasets.download.DownloadManager that can be used to

	dl_path = dl_manager.download_and_extract(_DATA_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"input_file": os.path.join(dl_path, self.config.name, "X.txt"),
	"label_file": os.path.join(dl_path, self.config.name, "Y.txt"),
	"label_level_1_file": os.path.join(dl_path, self.config.name, "YL1.txt"),
	"label_level_2_file": os.path.join(dl_path, self.config.name, "YL2.txt"),
	},
	)
	]

	def _generate_examples(self, input_file, label_file, label_level_1_file, label_level_2_file):
	"""Yields examples."""
	with open(input_file, encoding="utf-8") as f:
	input_data = f.readlines()
	with open(label_file, encoding="utf-8") as f:
	label_data = f.readlines()
	with open(label_level_1_file, encoding="utf-8") as f:
	label_level_1_data = f.readlines()
	with open(label_level_2_file, encoding="utf-8") as f:
	label_level_2_data = f.readlines()
	for i in range(len(input_data)):
	yield i, {
	"input_data": input_data[i],
	"label": label_data[i],
	"label_level_1": label_level_1_data[i],
	"label_level_2": label_level_2_data[i],
	}