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The features are considered the cornerstone of text summarization. The most important issue is what feature to be considered in a text summarization process. Including all the features in the summarization process may not be considered as an optimal solution. Therefore, other methods need to be deployed. In this paper, random five features used and(More)
Nowadays, many documents are available on the internet and are easy to access. Due to this wide availability, users can easily create a new document by copying and pasting. Plagiarism occurs when the content is copied without permission or citation. This paper introduces a plagiarism detection technique based on the Semantic Role Labeling (SRL). The(More)
Analysis on inter-document relationship is one of the important studies in multi document analysis. In this paper, we will focus on some special properties that multi document articles hold, specifically news articles. Information across news articles reporting on the same story are often related. Cross-document Structure Theory (CST) gives the relationship(More)
Generating high quality summary is representing the main challenge to researchers of automatic text summarizations. This study proposed an integrated artificial intelligence framework based on the evolutionary algorithm (EA) known by " Differential Evolution (DE) " to extract single document summaries. Four important subjects were considered: features(More)
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