Used Hierarchical Topic to Generate Multi-document Automatic Summarization

A concept of hierarchical topic is proposed for multi-document automatic summarization task, which used multi-layer topic tree structure to represent the text set. Each node in the topic tree represent specific topic and contains multiple similar sentences in the text set. The hierarchical topic str...

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Bibliographic Details
Main Authors: Xu Yong-Dong, Quan Guang-Ri, Zhang Ting-Bin, Wang Ya-Dong
Format: Conference Proceeding
Language:English
Subjects:
Clustering algorithms
Entropy
Feature extraction
Hierarchical topic
Multiple document automatic summarization
Natural lauguage processing
Partitioning algorithms
Periodic structures
Redundancy
Training
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Description
Summary:A concept of hierarchical topic is proposed for multi-document automatic summarization task, which used multi-layer topic tree structure to represent the text set. Each node in the topic tree represent specific topic and contains multiple similar sentences in the text set. The hierarchical topic structure may describe accurately the similarity between sentences at different levels of granularity. Therefore it can reflect the real content of the text set than single layer topic set. And can be used to find the important sentences in the important topic which can compose the summary of the text set. Concretely, a series of algorithms including building hierarchical topic tree, key sentences extraction based on hierarchical topic tree and summarization generation are proposed. The capability of summarization system is testified by sets of experiments and shows good result.
DOI:10.1109/ICICTA.2011.84