Year: 2011
Type: preprint
Abstract: When people explore and manage information, they think in terms of topics and themes. However, the software that supports information exploration sees text at only the surface level. In this paper we show how topic modeling -- a technique for identifying latent themes across large collections of documents -- can support semantic exploration. We present TopicViz, an interactive environment for information exploration. TopicViz combines traditional search and citation-graph functionality with a range of novel interactive visualizations, centered around a force-directed layout that links documents to the latent themes discovered by the topic model. We describe several use scenarios in which TopicViz supports rapid sensemaking on large document collections.
Source: arXiv (Cornell University)
Institution: Carnegie Mellon University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: III-COR+RI: Novel Statistical Models and Algorithms for Network Modeling, Mining and Reverse Engineering, VOSS: Coordination in Virtual Organizations, CAREER: Novel Statistical Models and Computational Algorithms for Evolutionary Genomics, SoCS: Collaborative Research: Information Farming: Intelligent Interfaces for an Online Production Community
OpenAlex ID: W4394653346