Er is een steeds sterkere tendens om onderzoeksgegevens te visualiseren in plaats van in tabellen weer te geven. Een belangrijk voordeel van visualisatie is dat de resultaten vaak direct duidelijk en eenvoudig te interpreteren zijn. Zo kan met behulp van meerdimensionele schaling de samenhang...

Perceptual maps are often used in marketing to visually study relations between two or more attributes. However, in many perceptual maps published in the recent literature it remains unclear what is being shown and how the relations between the points in the map can be interpreted or even what a...

In a recent article in JASIST, L. Leydesdorff and L. Vaughan (2006) asserted that raw cocitation data should be analyzed directly, without first applying a normalization such as the Pearson correlation. In this communication, it is argued that there is nothing wrong with the widely adopted...

Multidimensional scaling (MDS) is often used for the analysis of correlation matrices of items generated by a facet theory design. The emphasis of the analysis is on regional hypotheses on the location of the items in the MDS solution. An important regional hypothesis is the axial constraint...

In a recent paper in the Journal of the American Society for Information Science and Technology, Leydesdorff and Vaughan assert that raw cocitation data should be analyzed directly, without first applying a normalization like the Pearson correlation. In this report, it is argued that there is...

We present a new method for visualizing similarities between objects. The method is called VOS, which is an abbreviation for visualization of similarities. The aim of VOS is to provide a low-dimensional visualization in which objects are located in such a way that the distance between any pair...

Traditionally, recommender systems present recommendations in lists to the user. In content- and knowledge-based recommendation systems these list are often sorted on some notion of similarity with a query, ideal product specification, or sample product. However, a lot of information is lost in...