FURI | Spring 2020
Connecting the Dots: Towards Automated Dataset and Visualization Recommendation from News Articles
In this project, the team is investigating the efficacy of automatically recommending data visualizations to accompany a news story, even when there is no explicit data provided. To do this, the team is creating a data pipeline that combines natural language and machine learning operations, including document summarization, keyword extraction, dataset search and retrieval, and visualization recommendation. A series of user studies will be conducted to fine-tune the parameters of the pipeline, to evaluate how “best” to recommend data visualizations for text documents.
Hometown: Cupertino, California, United States
Graduation date: Spring 2021