Julia Wiedmann

Julia Wiedmann

Doctoral Student

Leaving date: 8th July 2019

Themes:

• Data, Knowledge and Action

Completed Projects:

• VADA

Interests

Julia is working on web data extraction. She is particularly interested in the template-independent extraction from the web using machine learning methods. She currently focuses on the event and product domain. Julia is particularly interested in web data extraction in the context of automatic knowledge base population.

Julia is currently working on automatically adding events from the web to the Diffbot Knowledge Graph.

Biography

Julia is a DPhil student in Computer Science at the University of Oxford. She previously completed her Master's degree in Computer Science at the University College London (UCL) and has a Bachelors degree in Business.

Selected Publications

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• Joint Learning of Structural and Textual Features for Event Extraction from the Web

  Julia Wiedmann

  In Processings of the Thirty−First AAAI Conference on Artificial Intelligence (AAAI−17) San Francisco. 2017.

  Details about Joint Learning of Structural and Textual Features for Event Extraction from the Web | BibTeX data for Joint Learning of Structural and Textual Features for Event Extraction from the Web | Download  (pdf) of Joint Learning of Structural and Textual Features for Event Extraction from the Web

Supervisor