Topic Mapping to Support Users in Literature Search

Abstract

This paper describes the design and development of the Topic Map, a visualization and user interaction component of a cloud-based tool, Archimedes. Archimedes is designed to help individuals and teams examine and organize the results of a literature search and use them to understand the space that they are researching. The Topic Map is a document surrogate, designed to help the user visualize the topic space represented by the search corpus. It shows frequently occurring but generally uncommon topics in a user’s workspace corpus. The Topic Mapper component generates the Topic Map automatically by extracting a list of topic phrases from the papers in the workspace, filtering and prioritizing what is displayed to the user based on a set of rules. It then visually distributes them in a two-dimensional space. This paper describes the motivation and design of the topic extraction implementation and its user interaction capabilities within Archimedes.