A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time

• Published in: Information processing & management Vol. 44; no. 4; pp. 1611 - 1623
• Main Authors: Quirin, A., Cordón, O., Santamaría, J., Vargas-Quesada, B., Moya-Anegón, F.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.07.2008; Elsevier; Elsevier Science Ltd
• Subjects: Algorithms; Bibliometrics. Scientometrics; Bibliometrics. Scientometrics. Evaluation; Citation analysis; Cocitation; Cocitation analysis; Exact sciences and technology; Graph shortest path algorithms; Information and communication sciences; Information processing; Information science. Documentation; Information visualization; Large scientific domain visual maps; Library and information science. General aspects; Matrix; Pathfinder algorithms; PFNETs; Sciences and techniques of general use; Social networks; Studies; Subject analysis; Visualization; Information visualization; Graph shortest path algorithms; Pathfinder algorithms; Cocitation analysis; Large scientific domain visual maps; PFNETs; Information mapping; Research field; Experimental result; Scientific research
• ISSN: 0306-4573; 1873-5371
• DOI: 10.1016/j.ipm.2007.09.005

In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI–JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O( n 4), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network). Although a previous improvement called Binary Pathfinder has already been proposed to speed up the original algorithm, its significant time complexity reduction is not enough for that aim. In this paper, we make use of a different shortest path computation from classical approaches in computer science graph theory to propose a new variant of the Pathfinder algorithm which allows us to reduce its time complexity in one order of magnitude, O( n 3), and thus to significantly decrease the run time of the implementation when applied to large scientific domains considering the parameter q = n − 1. Besides, the new algorithm has a much simpler structure than the Binary Pathfinder as well as it saves a significant amount of memory with respect to the original Pathfinder by reducing the space complexity to the need of just storing two matrices. An experimental comparison will be developed using large networks from real-world domains to show the good performance of the new proposal.