Improving Citation Mining

TitleImproving Citation Mining
Publication TypeConference Paper
Year of Publication2009
AuthorsAfzal, M. T., H. Maurer, W. - T. Balke, and N. Kulathuramaiyer
Conference Name1st International Conference on Networked Digital Technologies (NDT 2009)
Conference LocationOstrava, Czech Republic

In recent years the number of citations a paper is receiving, is seen more and more (maybe too much so) as an important indicator for the quality of a paper, the quality of researchers, the quality of journals, etc. Based on the number of citations a scholar has received over his lifetime or over the last few years various measures have been introduced. The number of citations (often without counting self-citations or citations from “minor” sources, in whatever way this may be defined), or some measurement based on the number of citations (like the h- or the g-factor) are being used to evaluate scholars; the citation index of a journal (again with a variety of parameters) is seen as measuring the impact of the journal, and hence the importance one assigns to publications there, etc. The number of measurements based on citation
numbers is steadily increasing, and their definition has become a science in itself. However, they all rest on finding all relevant citations. Thus, “citation mining tools” used for the ISI Web of Knowledge, the Citeseer citation index, Google scholar or software such as the “” software based on Google scholar, etc., are the critical starting points for all measurement efforts. In this paper we show that the current citation mining techniques do not discover all relevant citations. We propose a technique that increases accuracy substantially and show numeric evaluations for one typical journal. It is clear that in the absence of very reliable citation mining tools all current measurements based on citation counting should be considered with a grain of salt.

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