Scatter/Gather Browsing Communicates The Topic Structure Of A Very Large Text Collection

Abstract

Scatter/Gather is a cluster-based browsing technique for large text collections. Users are presented with automatically computed summaries of the contents of clusters of similar documents and provided with a method for navigating through these summaries at different levels of granularity. The aim of the technique is to communicate information about the topic structure of very large collections. We tested the effectiveness of Scatter/Gather as a simple pure document retrieval tool, and studied its effects on the incidental learning of topic structure. When compared to interactions involving simple keyword-based search, the results suggest that Scatter/Gather induces a more coherent conceptual image of a text collection, a richer vocabulary for constructing search queries, and communicates the distribution of relevant documents over clusters of documents in the collection.