PhD Opportunity

Information Retrieval and Text Summarisation for mobile devices

Mobile devices such as smart phones and PDAs have become increasing popular in recent years. Routinely, such devices are now used to browse the internet for news feeds, return search engine results or to access email. Due to the limited screen size and resolution supported by such devices an issue arises as to how to effectively recognise, organise, and display the most relevant information to users.

 

One preliminary idea is to evaluate the whole document and pick the most important sentences or paragraphs within the available space limits of the screen. More sophisticated summarisation algorithms are able to generate text summaries automatically by intelligently parsing documents. Indeed, this is an area that has received interest within the wider community [1-3], however, it is evident that further research is required to advance the currently available solutions.

 

This project can provide aims to investigate this area to gain an understanding of the state-of-the-art and to advance current approaches.

Objectives:

  1. Carry out a comprehensive literature review on text summarization for mobile devices.
  2. Develop a number of experimental algorithms to advance the state-of-the-art approaches.
  3. Evaluate the algorithms in both real and simulated environments.
  4. Disseminate the outcomes.

 

References

Claudio Carpineto, Stefano Mizzaro, Giovanni Romano, Matteo Snidero Mobile information retrieval with search results clustering: Prototypes and evaluations. Journal of the American Society for Information Science, Volume 60, Issue 5, February 2009, Pages 877 - 895.


Simon Sweeneya, Fabio Crestani, and David E. Losada 'Show me more': Incremental length summarisation using novelty detection. Information Processing & Management, Volume 44, Issue 2, March 2008, Pages 663-686
Jahna Otterbacher, Dragomir Radev, and Omer Kareem Hierarchical text summarization for WAP-enabled mobile devices. Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, Salvador, Brazil, 2006.

Personnel Involved

First Supervisor: Wu, S Dr
Second Supervisor: Wang, H Dr

Collaboration: This project does not involve collaboration with another establishment

Synopsis:

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