Organisations now frequently rely on virtual collaboration through the use of computer technology. After a sequence of meetings, participants may only need to refer to the most important points rather than the whole meeting proceedings. This paper addresses the need for automated meeting summarisation in virtual meeting systems. An extraction approach to summarisation is adopted and a new algorithm is proposed by extending the TextRank algorithm to include constructs representing the structure of the meeting. This helps extract the most relevant sentences from the meeting transcript. The proposed method was evaluated in the context of student-tutor meetings. Results show that harnessing and utilising the structure of a virtual meeting can lead to more relevant automated summaries.
|Title of host publication||2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD)|
|Number of pages||6|
|ISBN (Electronic)||978-1-5090-6199-0, 978-1-5090-6198-3|
|Publication status||Published - 1 Apr 2017|
|Event||IEEE 21st International Conference on Computer Supported Cooperative Work in Design - University of Victoria, Wellington, New Zealand|
Duration: 26 Apr 2017 → 28 Apr 2017
|Conference||IEEE 21st International Conference on Computer Supported Cooperative Work in Design|
|Period||26/04/17 → 28/04/17|
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- Brain modeling
- virtual meeting summarisation
- structured meeting