VITALITY: Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics

@article{Narechania2022VITALITYPS,
  title={VITALITY: Promoting Serendipitous Discovery of Academic Literature with Transformers \& Visual Analytics},
  author={Arpit Narechania and Alireza Karduni and Ryan Wesslen and Emily Wall},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2022},
  volume={28},
  pages={486-496}
}
There are a few prominent practices for conducting reviews of academic literature, including searching for specific keywords on Google Scholar or checking citations from some initial seed paper(s). These approaches serve a critical purpose for academic literature reviews, yet there remain challenges in identifying relevant literature when similar work may utilize different terminology (e.g., mixed-initiative visual analytics papers may not use the same terminology as papers on model-steering… 

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References

SHOWING 1-10 OF 84 REFERENCES
PaperVis: Literature Review Made Easy
TLDR
The work, called PaperVis, endeavors to provide a user‐friendly interface to help users quickly grasp the intrinsic complex citation‐reference structures among a specific group of papers by modifying the existing Radial Space Filling and Bullseye View techniques to arrange involved papers as a node‐link graph.
VisualBib: Narrative Views for Customized Bibliographies
  • A. Dattolo, M. Corbatto
  • Computer Science
    2018 22nd International Conference Information Visualisation (IV)
  • 2018
TLDR
VisualBib is introduced, a Web application prototype conceived to support researchers who wish to create, modify, visualize and share bibliographies, which are represented using holistic, aggregated and graphical views.
VISPubComPAS: a comparative analytical system for visualization publication data
TLDR
This work provides comprehensive visual analysis of research affiliations and domain experts based on papers accepted by the IEEE VIS from 1990 to 2018 and designs and implements VISPubComPAS, a requirement-driven analysis system to help users discover top affiliations or experts of required keywords.
CiteRivers: Visual Analytics of Citation Patterns
TLDR
This technique facilitates user-steered aggregation of citations which are linked to the content of the citing publications using a highly interactive visualization approach and enable users to analyze citation patterns, spot trends, and track long-term developments.
Visualization as Seen through its Research Paper Keywords
TLDR
A comprehensive multi-pass analysis of visualization paper keywords supplied by authors for their papers published in the IEEE Visualization conference series between 1990-2015 derived a set of visualization topics that can facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization.
Visual Analysis and Dissemination of Scientific Literature Collections with SurVis
TLDR
SurVis is a more accessible visual analytics system that is ready to disseminate a carefully surveyed literature collection that employs a set of selectors that enable users to filter and browse the literature collection as well as to control interactive visualizations.
GlassViz: Visualizing Automatically-Extracted Entry Points for Exploring Scientific Corpora in Problem-Driven Visualization Research
TLDR
A model and a proof-of-concept visual text analytics (VTA) tool are developed to enhance document discovery in a problem-driven visualization research (PDVR) context and captures the cognitive model followed by domain and visualization experts by analyzing the interdisciplinary communication channel.
Taking Word Clouds Apart: An Empirical Investigation of the Design Space for Keyword Summaries
In this paper we present a set of four user studies aimed at exploring the visual design space of what we call keyword summaries: lists of words with associated quantitative values used to help
Speculative Practices: Utilizing InfoVis to Explore Untapped Literary Collections
TLDR
This paper exemplifies how information visualization supports speculative thinking, hypotheses testing, and preliminary interpretation processes as part of literary research and suggests a design space for visualizing literary collections that is defined by their academic and public relevance.
A Conference Paper Exploring System Based on Citing Motivation and Topic
TLDR
A paper exploring system that can confirm the purpose of specific papers being cited by other authors and help identify the characteristics of related studies based on the target papers is provided.
...
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