Modelling on web summarisation based on structure analysis and vectorisation similarity
by Kai Gao; Hong-xia Ma; Radha Ganesan
International Journal of Modelling, Identification and Control (IJMIC), Vol. 20, No. 4, 2013

Abstract: With the rapid development of the internet, the useful information extraction has become increasingly important. Web summarisation, as the art of abstracting key contents from huge web data, has become an integral part of search engines and digital libraries. As the weighted keywords can be considered as condensed versions of the content, on the basis of the statistics, this paper proposes a novel summarisation approach based on structure analysis and keyword vectorisation similarity. The structure vector space model, the candidate selection and the summarisation generation are also applied in this novel approach. The experimental results show that this approach is feasible. Existing problems and further works are also presented at the end of the paper.

Online publication date: Sat, 27-Sep-2014

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