Semantically faceted navigation with topic pies

Faceted search allows navigating through large collections along different dimensions in order to find relevant objects efficiently. Traditional faceted search systems often suffer from a lack of usability; furthermore facets are often static and independent from the search result set. In this paper, we present a dynamic semantic topical faceting approach. It uses a pie menu called topic pie that allows visualisation of facets and user interaction. Depending on the search query, the topic pie presents a set of topics and major topics which help the user to drill down the search result set to relevant objects efficiently as well as to browse exploratively through the collection. The underlying algorithm optimises the conflicting goals relevance and diversity while avoiding information overload. It reveals a good performance on large data sets. As our use-case, we chose literature research in scientific libraries. An evaluation shows major advantages of our approach compared to state-of-the-art faceted search techniques in nowadays library portals.