GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory Search

Author:

Guo Mengtian1ORCID,Zhou Zhilan1ORCID,Gotz David1ORCID,Wang Yue1ORCID

Affiliation:

1. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Abstract

When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. Building this mental model can be challenging as it requires not only finding relevant documents but also synthesizing important concepts and the relationships that connect those concepts both within and across documents. This article describes a novel interactive approach designed to help users construct a mental model of an unfamiliar information space during exploratory search. We propose a new semantic search system to organize and visualize important concepts and their relations for a set of search results. A user study (n=20) was conducted to compare the proposed approach against a baseline faceted search system on exploratory literature search tasks. Experimental results show that the proposed approach is more effective in helping users recognize relationships between key concepts, leading to a more sophisticated understanding of the search topic while maintaining similar functionality and usability as a faceted search system.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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