PUREsuggest: Citation-based Literature Search and Visual Exploration with Keyword-controlled Rankings

TL;DR

PUREsuggest is a citation-based literature search tool that visually explains ranking processes and allows user steering via keywords, enhancing literature collection and expert identification.

Contribution

It introduces a transparent, keyword-controlled citation suggestion system with visual network exploration for literature search and collection building.

Findings

Effective visualization of citation rankings.

User study shows improved search strategies.

System supports building and updating literature collections.

Abstract

Citations allow quickly identifying related research. If multiple publications are selected as seeds, specific suggestions for related literature can be made based on the number of incoming and outgoing citation links to this selection. Interactively adding recommended publications to the selection refines the next suggestion and incrementally builds a relevant collection of publications. Following this approach, the paper presents a search and foraging approach, PUREsuggest, which combines citation-based suggestions with augmented visualizations of the citation network. The focus and novelty of the approach is, first, the transparency of how the rankings are explained visually and, second, that the process can be steered through user-defined keywords, which reflect topics of interests. The system can be used to build new literature collections, to update and assess existing ones, as well as to use the collected literature for identifying relevant experts in the field. We evaluated the recommendation approach through simulated sessions and performed a user study investigating search strategies and usage patterns supported by the interface.