info:eu-repo/semantics/bachelorThesis
An interactive visualization method for scientific literature exploration based on textual and image content
Fecha
2020Autor
Gomez Nieto, Erick Mauricio
Institución
Resumen
Exploring digital libraries of scientific articles is an essential task to the research
community, in both academia and industry. Traditional paradigm presents
briefly textual information by article, in a list-based layout without almost visual
resources. This design does not allow exploratory operations – as clustering,
filtering, or aggregating – on the results delivered by the digital library. Consider
the case where the analyst has a referenced article and wants to look for related
works. Except for the articles which share citations or common keywords, the
retrieved results will be limited to those which fulfill a syntactic match. If
instead of having an article as a reference, the user has an image, the process
of finding and explore articles with similar content becomes almost non-viable.
In this project we propose a visual analytic tool for exploring and analyze
scientific document collections by combining image and textual information
extracted from articles. Our method relies on the interaction between a ContentBased Image Retrieval (Content-based image retrieval (CBIR)) widget and an
interactive multidimensional projection method for mapping similarity relations
in 2D space. We exploit other visual resources for representing author and
topic information articles according to the selections and preferences of the
user. Moreover, a user exploration log is stored for comparing two or more
timestamps during the information extraction process, allowing to discover
patterns and relations hidden. The effectiveness of our methodology is shown
through two case studies and user evaluation, which attest to the usefulness of
the proposed framework in exploring scientific document collections.