datasets

Datasets

Requirements

NOTE: this should automatically be done by running setup script in the root folder.

This class requires the ake-datasets repository, which contains a parsed collection of keyword extraction datasets. To download it, clone it in this folder with:

$ git clone https://github.com/boudinfl/ake-datasets.git

Watch out, it will download around 11 GB of data.

Usage

In order to use the Dataset class, import it by giving it as its argument the name of the dataset you want to use, either from the available datasets or by using the path of a custom dataset.

Example usage from the root folder:

from datasets.datasets import Dataset

# initialize dataset class and get texts and labels
ds = Dataset('DUC-2001')

# this will print out the 10th text in the collection
print(ds.texts[10])

# this will print the list of reference keywords for the 10th text
print(ds.labels[10])

Available Datasets

Currently, all datasets in this table are available.

dataset	lang	nature	train	dev	test	Annotation	#kp (test)	#words (test)
NUS [1]	en	Full papers	-	-	211	A+R	11.0	8398.3
Inspec [2]	en	Abstracts	1000	500	500	I (uncontr)	9.8	134.6
KDD [3]	en	Abstracts	-	-	755	A	4.1	190.7
WWW [3]	en	Abstracts	-	-	1330	A	4.8	163.5
DUC-2001 [4]	en	News	-	-	308	R	8.1	847.2
500N-KPCrowd [5]	en	News	450	-	50	R	46.2	465.3

Where annotations were produced by authors (A), readers (R) or professional indexers (I).

Custom Datasets

You can use any custom dataset that is in CSV format. The file should contain all texts in a column named text, and all labels in a column named labels. The file may be placed anywhere inside this directory.

The labels for a text are supposed to be a list of keyphrases, which in the CSV file should appear as a single string where the keyphrases are separated by the pipe | character. For instance, one entry in the label column could look like:

dog|walk in the park|sun|ice-cream|hot weather

The custom dataset can then be loaded using the Dataset class by using:

ds = Dataset('file/path.csv')

Where the file path is relative to this directory.

References

1. Keyphrase Extraction in Scientific Publications. Thuy Dung Nguyen and Min-Yen Kan. In Proceedings of International Conference on Asian Digital Libraries 2007. p. 317-326.

2. Improved automatic keyword extraction given more linguistic knowledge. Anette Hulth. In Proceedings of EMNLP 2003. p. 216-223.

3. Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach. Cornelia Caragea, Florin Bulgarov, Andreea Godea and Sujatha Das Gollapalli. In Proceedings of EMNLP 2014. pp. 1435-1446.

4. Single Document Keyphrase Extraction Using Neighborhood Knowledge. Xiaojun Wan and Jianguo Xiao. In Proceedings of AAAI 2008. pp. 855-860.

5. Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization. Marujo, L., Gershman, A., Carbonell, J., Frederking, R., & Neto, J. P. In Proceedings of LREC 2012.