Automatic Texts Summarization: Current State of the Art
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Keywords

Automatic text summarization, Clustering, RST, Graph theory, Latent semantic analysis, Fuzzy logic, Machine learning, Topic identification.

How to Cite

ALAMI, N. ., MEKNASSI, M. ., & RAIS, N. . (2015). Automatic Texts Summarization: Current State of the Art. Journal of Asian Scientific Research, 5(1), 1–15. https://doi.org/10.18488/journal.2/2015.5.1/2.1.1.15

Abstract

To facilitate the task of reading and searching information, it became necessary to find a way to reduce the size of documents without affecting the content. The solution is in Automatic text summarization system, it allows, from an input text to produce another smaller and more condensed without losing relevant data and meaning conveyed by the original text. The research works carried out on this area have experienced lately strong progress especially in English language. However, researches in Arabic text summarization are very few and are still in their beginning. In this paper we expose a literature review of recent techniques and works on automatic text summarization field research, and then we focus our discussion on some works concerning automatic text summarization in some languages. We will discuss also some of the main problems that affect the quality of automatic text summarization systems.

https://doi.org/10.18488/journal.2/2015.5.1/2.1.1.15
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