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Generation of non-redundant summary based on sum of similarity

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2 Author(s)
Yang Sun ; Div. of Electron. & Inf. Eng., Chonbuk Nat. Univ., Chonju, South Korea ; Soon Cheol Park

This paper proposes an efficient method to extract the most important and non-redundant sentence segments based on sum of similarity. The new characteristics of our method are listed as follows: 1) we use preprocessing to delete the additional information (comma parenthesis) that won't turn up in the summarization; 2) redesign the vector similarity between a pair of sentences by using sum of similarity; 3) in order to maximize topic diversity, we use a strikingly different redundancy reducing ways other than MMR.. Experimental results show that our approach compares favorably with some other summary systems.

Published in:

International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II  (Volume:2 )

Date of Conference:

4-6 April 2005