Context-Based Persian Multi-document Summarization (Global View)

Poormasoomi, Asef; Kahani, Mohsen; Yazdi, Saeed Varasteh; Kamyar, Hossein

doi:10.1109/ialp.2011.53

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In extractive summarization, there are two main considerations for building a summary, namely how to choose the most important information appearing in the source documents [4,5]and how to present the chosen information in a coherent manner in the resulting summary [6,7]. The former has received much attention in previous research, using both statistical and/or linguistic approaches.…”

Section: Introductionmentioning

confidence: 99%

Improving coherence by reordering the output of extractive summarization using Centering Theory through genetic algorithm

Yuliawati

Manurung

2013

2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS)

View full text Add to dashboard Cite

Extractive summarization is a widely studied and fairly easy to implement technique. It works by choosing the most important parts of a document(s) as a summary. However, this can lead to a lack of coherence in the summary itself. In this study, the principle of continuity in Centering Theory is used to maintain the entity coherence between subsequent sentences obtained from extractive news summarizer. Simultaneously, the relative order of sentences belonging to the same source document is maintained. These two considerations are implemented as fitness functions for a genetic algorithm that is used to obtain the optimal ordering of sentences in the summary. Based on the results of our study involving human judgment, a weighted fitness function combining 75% continuity and 25% relative order yields the most acceptable sentence ordering.

show abstract