Making the H-index more relevant: A step towards standard classes for citation classification

Abdullatif, Mohammad

doi:10.1109/icdew.2013.6547476

Cited by 5 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Manual citation function classification has been proposed, but subsequently automated classification became inevitable due to the large number of publications produced on a daily basis [3]. Automated citation function classification has been carried in the literature into two ways; the first way is the use of rule based methods where domain experts developed rules that were coded into computer programs to perform citation function classification [5]. The rules were created based on a set of human labeled citations where each citation was labeled with a function or label revealing the related purpose.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Scheme for Citation Classification based on Convolutional Neural Networks

Bakhti¹,

Niu²,

Nyamawe³

2018

International Conferences on Software Engineering and Knowledge Engineering

View full text Add to dashboard Cite

Automated classification of citation function in scientific text is a new emerging research topic inspired by traditional citation analysis in applied linguistic and scientometric fields. The aim is to classify citations in scholarly publication in order to identify author's purpose or motivation for quoting or citing a particular paper. Several citation schemes have been proposed to classify the citations into different functions. However, it is extremely challenging to find standard scheme to classify citations, and some of the proposed schemes have similar functions. Moreover, most of previous studies mainly used classical machine learning methods such as support vector machine and neural networks with a number of manually created features. These features are incomplete and suffer from time-consuming and error prone weakness. To address these problems, we present a new citation scheme with less functions and propose a deep learning model for classification. The citation sentences and author's information were fed to convolutional neural networks to build citation and author representations. A corpus was built using the proposed scheme and a number of experiments were carried out to assess the model. Experimental results have shown that the proposed approach outperforms the existing methods in term of accuracy, precision and recall.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Previous studies on automated citation function classification commonly used rule-based and supervised machine learning methods [5], [7]. However, the rule-based techniques do not generalize well for citations that have never been seen by the domain experts.…”

Section: Introductionmentioning

confidence: 99%