Overview
Topic status: We're looking for students to study this topic.
This project aims to investigate the use of multi-document summarisation techniques for producing summaries of clinical documents. This will provide doctors and medical practitioners with a tool that can support and enhance their activities.
Objectives
- to develop state-of-the-art summarisation techniques
- to use natural language processing methods to support summarisation
- to test summarisation techniques over domain specific data, i.e. clinical reports
- to evaluate summarisation techniques.
Requirements
- programming skills in Java or C++
- ability to analyze and interpret results
- knowledge of one subject between information retrieval/machine learning/natural language processing is required.
What you will learn
- state-of-the-art document summarisation techniques
- to evaluate summarisation techniques.
Scholarship
An honours scholarship or masters top-up will be available for the student working on this topic. It will also open to PhD opportunities with CSIRO.
References
- S. Afantenos et al, “Summarization from medical documents: a survey”, Journal of Artificial Intelligence in Medicine, 2005.
- D. Das, A. Martins, “A Survey on Automatic Text Summarization”, CMU technical report, 2007.
- Study level
- Masters, Honours
- Supervisors
- QUT External Guido Zuccon
- Organisational unit
Science and Engineering Faculty
- Research area
- Keywords
- Summarisation, Medical Records
- Contact
-
For more information contact Dr. Laurianne Sitbon
Dr Laurianne Sitbon
