  Log analysis in Web search showed that user sessions often contain several
different topics. This means sessions need to be segmented into parts which
handle the same topic in order to give appropriate user support based on the
topic, and not on a mixture of topics. Different methods have been proposed to
segment a user session to different topics based on timeouts, lexical analysis,
query similarity or external knowledge sources. In this paper, we study the
problem in a digital library for the social sciences. We present a method based
on a thesaurus and a classification system which are typical knowledge
organization systems in digital libraries. Five experts evaluated our approach
and rated it as good for the segmentation of search sessions into parts that
treat the same topic.
