Scientific reference mining using semantic information through topic modeling.

Ali Daud; Muhammad Akram Shaikh; Altaf Hussain Rajpar

No Detail Found!

Scientific reference mining using semantic information through topic modeling.

Author(s)

Ali Daud Department of Computer Science & Technology, Tsinghua University, Beijing, China

Muhammad Akram Shaikh Department of Computer Systems & Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan

Altaf Hussain Rajpar Department of Mechanical Engineering, Quaid-e-Awam University of Engineering, Science & Technology, Shaheed Benazir Bhuttoabad, Nawabshah, Pakistan

Abstract

This paper addresses one time-consuming task in preparing scientific papers for finding appropriate citations (references). In the past this task was usually performed manually or by using links information of papers. Link information only used title of paper and ignored the semantic-based text information present in the paper contents. Due to overlaps between different fields e.g. in computer science only title of a paper cannot be real representative of different other hidden topics of that paper. The authors thought that it was necessary to model the semantic information present in papers to provide more appropriate citations by capturing hidden topics. In this paper, the authors addressed this issue by modeling citations on the basis of latent topics preset in the papers. Latent topics can provide semantic correlations present between the papers. The authors proposed a topic modeling approach in which each citation of a paper was represented as a probability distribution over latent topics, and each latent topic is represented as a probability distribution over words of paper for that topic, which can provide more appropriate citations for a given paper. Experimental results on citeceer corpus shows the effectiveness of proposed approach and detailed interpretation of results reveals interesting information about SR (Scientific Recommendation).

Publication Details

Page(s) 253-262

DOI DOI not available

Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 28, Issue: 2, Year: 2009

Request the full text from PASTIC

Citations

Downloads

Views