Sub-topic Segmentation in Multi-document

DOI

10.2991/iccia.2012.379How to use a DOI?

Keywords

Multi-document Summarization, Sub-topic Segmentation,Maximum tree algorithm

Abstract

The similar sentences in multi-document set are combined into one class, and each class is one sub-topic. Describing the sub-topics from the perspective of understanding makes the multi-document summarization become the one with greater coverage and less redundancy. This paper presents a sub-topic segmentation method based on maximum tree algorithm. And based on sentences similarity matrix, maximum tree is calculated, as well as the sub-topic segmentation is realized through the analysis of the different communities for the sub-topic. The experiment shows that the method achieves the desired result.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaoyan Yun
AU  - Wei Teng
PY  - 2014/05
DA  - 2014/05
TI  - Sub-topic Segmentation in Multi-document
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1529
EP  - 1531
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.379
DO  - 10.2991/iccia.2012.379
ID  - Yun2014/05
ER  -