Thesis Topic Details

Topic ID:
739
Title:
Online text summarization
Supervisor:
Raymond Wong
Research Area:
Natural Language Processing, Information Retrieval, Web Applications
Associated Staff
Assessor:
Wei Wang
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
Yes
Industrial:
No
Pre-requisites:
Good knowledge on data structures and algorithms; good programming skill
Description:
The current information overload problem and increasing popularity of mobile devices has called for the need to develop an efficient online automatic text summarization system.

This project will extend our previous work on an efficient sentence-based extraction summarizer which can be used for offline text summarization. Lexical chains were used as a basis and knowledge resources such as WordNet and a sentence boundary disambiguation tool were integrated to the system for better performance.

Three different summary extraction heuristics were implemented and compared so far. An intrinsic evaluation which involved the comparison of our summarizer with a commercial product to the human written abstracts was performed. The results obtained have been encouraging, and it is found that our system favors the human judgement than the other system.

However, the algorithm developed so far demonstrated a linear runtime behavior. This needs to be extended and optimized in order for online applications.

You will work with a small group of research students in this project. A previous report on this project can be found at:
ftp://ftp.cse.unsw.edu.au/pub/doc/papers/UNSW/0311.pdf
Comments:
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Past Student Reports
 
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