An extractive approach for uyghur text summarization

作者：Tohti Turdi; Yilahun Hankiz; Hamdulla Askar^*

来源：International Journal of Hybrid Information Technology, 2016, 9(4): 69-82.

DOI：10.14257/ijhit.2016.9.4.07

• Extractive approach
• Extractive summarizations
• Frequent pattern growth
• Including degrees
• Multi-feature fusion
• Redundant sentence removing
• Sentence alignment
• Sentence similarity

This paper studies Uyghur single text summarization and proposes some of new or improved approaches in the aspects of keyword extraction and evaluation, sentence selection and redundancy removal, also in readability improvement and so on. Proposes an improved frequent pattern-growth approach to extract the semantic strings which perfect both on its semantics and structural integrity, to evaluate this strings uses multi- feature fusion approach and select most important ones as keywords to describe the text theme effectively. In the aspect of sentence similarity and redundancy removal, proposes the idea of theme including degree, so as to effectively remove the redundant sentences and improves the summary quality significantly. Also introduces sentence alignment between the texts that after being stemming and original text, so as to solve the problems that summary naturalness, coherence and comprehensibility decline and other issues caused by stemming process.

• 出版日期2016