  Algorithmic classification of research publications has been created to study
different aspects of research. Such classifications can be used to support
information needs in universities for decision making. However, the
classifications have foremost been evaluated quantitatively regarding their
content, but not qualitatively regarding their feasibility in a specific
context. The aim of this study was to explore and evaluate the usefulness of
such classifications to users in the context of exploring an emerging research
area. I conducted four interviews with managers of a project aimed to support
research and application of artificial intelligence at the Swedish medical
university Karolinska Institutet. The interviews focused on the information
need of the managers. To support the project, a classification was created by
clustering of publications in a citation network. A cluster map based on this
classification was provided to the project leader and one interview focused on
the use of the classification in the project in relation to the stated
information needs. The interviews showed that the aim of the project was to
improve competence, enhance communication between researchers and develop
support structures. Getting an overview of artificial intelligence at the
university and information about who is doing what was important to fulfill
this aim. The cluster map was used to support activities conducted by the
project leader, such as interviews and information gathering. It was also used
to get overview and display of AI research at KI. Interpretation was found to
be challenging in some cases. The interactivity of the map facilitated
interpretation. This study was small in scope, but it provides one piece of
knowledge about the information needs related to algorithmic classifications.
