Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Keyword Extraction
  2.1. Semantic String Extraction
  2.2. Semantic String Evaluation and Keyword Extraction
 3. Key Sentence Selection and Redundancy Removal
  3.1. Sentence Weighting
  3.2. Sentence Redundancy Removal
 4. Summary Organization
 5. Experiments and Analysis
  5.1. Corpus for Experiment
  5.2. Time Efficiency
  5.3. Summary Quality
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Turdi Tohti [ School of Information Science and Engineering, Xinjiang University, Urumqi, china ]
• Hankiz Yilahun [ School of Information Science and Engineering, Xinjiang University, Urumqi, china ]
• Askar Hamdulla [ School of Software, Xinjiang University, Urumqi，China 830046 ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605