Similarity measures for document mapping: A comparative study on the level of an individual scientist

Abstract

This paper investigates the utility of the Inclusion Index, the Jaccard Index and the Cosine Index for calculating similarities of documents, as used for mapping science and technology. It is shown that, provided that the same content is searched across various documents, the Inclusion Index generally delivers more exact results, in particular when computing the degree of similarity based on citation data. In addition, various methodologies such as co-word analysis, Subject-Action-Object (SAO) structures, bibliographic coupling, co-citation analysis, and selfcitation links are compared. We find that the two former ones tend to describe rather semantic similarities that differ from knowledge flows as expressed by the citation-based methodologies.

An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field

“…Although the weight of a thematic nexus can be measured with other similarity measures (e.g., the Jaccard index or Salton's cosine), the inclusion index has the advantage of being more useful to measure similar sets, in comparison to the Jaccard or cosine index, since it is not biased by the number of items as the latter are (Sternitzke & Bergmann, 2009). The inclusion index has also been used as an overlap measure in the field of information retrieval ( van Eck & Waltman, 2009).…”

Mapping of important international academic awards

“…Then, based on these items, the similarities between the documents are computed by measures such as Jaccard index, inclusion index, cosine index, and association strength. Finally, the similarities are visualized by means of multivariate analyses (Sternitzke and Bergmann 2009). A number of software tools have been developed to conduct science mapping analysis (Cobo et al 2011).…”

SAO network analysis of patents for technology trends identification: a case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells

“…Moehrle et al (2005) suggested a method that uses inventor profiles to support human resource decisions, and Bergmann et al (2008) used patent similarities to analyze the risk of patent infringement. Recently, some research has focused on how to improve the accuracy of comparison methods for patent similarities by using the SAO model (Moehrle 2010;Sternitzke and Bergmann 2009). …”