A Method to Automatically Identify the Results from Journal Articles

Gabb, Henry A.; Lucic, Ana; Blake, Catherine

Permalink

https://hdl.handle.net/2142/73645 Copy

Description

Title

A Method to Automatically Identify the Results from Journal Articles

Author(s)

• Gabb, Henry A.
• Lucic, Ana
• Blake, Catherine

Issue Date

2015-03-15

Keyword(s)

• data analytics and evaluation
• text/data/knowledge mining

Abstract

The idea of automating systematic reviews has been motivated by both advances in technology that have increased the availability of full-text scientific articles and by sociological changes that have increased the adoption of evidence-based medicine. Although much work has focused on automating the information retrieval step of the systematic review process with a few exceptions the information extraction and analysis have been largely overlooked. In particular, there is a lack of systems that automatically identify the results of an empirical study. Our goal in this paper is to fill that gap. We frame the problem as a classification task and employ three different objective, domain-independent feature selection strategies and two different classifiers. Additionally, special attention is paid to the selection of the data set used in this experiment, the feature selection metrics as well as the classification algorithms, and parameters of the algorithms used for classification in order to show the situatedness of this experiment and its dependence on each of the three parameters.

Publisher

iSchools

Series/Report Name or Number

iConference 2015 Proceedings

Type of Resource

text

Language

English

Permalink

http://hdl.handle.net/2142/73645

Copyright and License Information

Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

Owning Collections