Two-handed volumetric document corpus management

Abstract

To find a document in the sea of information, you must embark on a search process, usually computer-aided. In the traditional information retrieval model, the final goal is to identify and collect a small number of documents to read in detail. In this case, a single query yielding a scalar indication of relevance usually suffices. In contrast, document corpus management seeks to understand what is happening in the collection of documents as a whole (i.e. to find relationships among documents). You may indeed read or skim individual documents, but only to better understand the rest of the document set. Document corpus management seeks to identify trends, discover common links and find clusters of similar documents. The results of many single queries must be combined in various ways so that you can discover trends. We describe a new system called the Stereoscopic Field Analyzer (SFA) that aids in document corpus management by employing 3D volumetric visualization techniques in a minimally immersive real-time interaction style. This interactive information visualization system combines two-handed interaction and stereoscopic viewing with glyph-based rendering of the corpora contents. SFA has a dynamic hypertext environment for text corpora, called Telltale, that provides text indexing, management and retrieval based on n-grams (n character sequences of text). Telltale is a document management and information retrieval engine which provides document similarity measures (n-gram-based m-dimensional vector inner products) visualized by SFA for analyzing patterns and trends within the corpus.