Paper recommendation using citation proximity in bibliographic coupling

Raja HABIB; Muhammad Tanvir AFZAL

Makale detayları

Paper recommendation using citation proximity in bibliographic coupling

Yazarlar:

Raja HABIB | Muhammad Tanvir AFZAL

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2708-2718

Belge Tipi:

Makale

Yayın Tarihi:

7/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000736061

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Research paper recommendation has been a hot research   area for the last few decades. Thus far, numerous different paper   recommendation approaches have been proposed. Some of these include methods   based on metadata, content similarity, collaborative filtering, and citation   analysis, among others. Citation analysis methods include bibliographic   coupling and co-citation analysis. Much research has been done in the area   of co-citation analysis. Researchers have also performed experiments using   the proximity of in-text citations in co-citation analysis and have found   that it improves the accuracy of paper recommendation. In co-citation   analysis, the similarity is discovered based on the frequency of co-cited   papers in different research papers and those citing papers may belong to   different areas. However, when proximity is used to calculate co-citation,   the accuracy of recommendations improves significantly. Bibliographic   coupling finds bibliographic coupling strength based on the common   references between two papers. In bibliographic coupling, a large number of   common references of two papers means that they belong to the same area,   unlike co-citation analysis, in which there is a possibility that the citing   papers may belong to different areas. Based on the observation that with the   use of proximity analysis the accuracy in cases of co-citation analysis has   improved, this paper investigates if the accuracy of paper recommendation   can be further improved by using proximity analysis in bibliographic   coupling. This paper proposes an approach that extends the traditional   bibliographic coupling by exploiting the proximity of in-text citations of   bibliographically coupled articles. The proposed approach takes into account   the proximity of in-text citations by clustering the in-text citations using   a density-based algorithm called DBSCAN. Experiments on a data set of   research papers are presented to show that there is a substantial increase   in accuracy of the recommendations produced by DBSCAN based on proximity   analysis of in-text citations compared to traditional bibliographic coupling   and content-based approaches.

Makale detayları

Paper recommendation using citation proximity in bibliographic coupling

Yazarlar: Raja HABIB | Muhammad Tanvir AFZAL

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2708-2718

Belge Tipi: Makale

Yayın Tarihi: 7/2017

Belge Dili: Türkçe

Document ID (Org No.): 2000736061

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Raja HABIB | Muhammad Tanvir AFZAL

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2708-2718

Belge Tipi:

Makale

Yayın Tarihi:

7/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000736061

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632