Eugene Agichtein and Qi Guo have developed:
a new class of search behavior models that also exploit fine-grained user interactions with the search results. We show that mining these interactions, such as mouse movements and scrolling, can enable more effective detection of the user’s search goals.
Their paper, Ready to Buy or Just Browsing? Detecting Web Searcher Goals from Interaction Data describes how light-weight mouse tracking can yield valuable information about users. (Contrast that with expensive eye tracking approaches.)
If you like that paper, see: Inferring Web Searcher Intent Tutorial and the bibliography of publications.
The design of a successful topic map interface is going to start and stop with user preferences. How fast or clever your topic map application may be, if users don’t want to use it, they won’t. That, by the way, is the definition of a unsuccessful application.