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An Ensemble Approach for Semantic Assessment of Summary Writings

机译:摘要写作语义评估的整体方法

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摘要

Computer-assisted assessment of summary writings is a challenging area which has recently attracted much interest from the research community. This is mainly due to the advances in other areas such as information extraction and natural language processing which have made automatic summary assessment possible. Different techniques such as Latent Semantic Analysis, $n$-gram co-occurrence and BLEUhave been proposed for automatic evaluation of summaries. However, these techniques are unable to achieve good performance. In this paper, we propose an ensemble approach, that integrates two of the most effective summary evaluation techniques, LSA and n-gram co-occurrence, for improving the accuracy of automatic summary assessment. The performance of the proposed ensemble approach has shown that it is able to achieve high accuracy and improve theperformance quite substantially compared with other existingtechniques.
机译:摘要摘要的计算机辅助评估是一个具有挑战性的领域,最近引起了研究界的极大兴趣。这主要归因于其他领域的进步,例如信息提取和自然语言处理,这使得自动摘要评估成为可能。已经提出了诸如潜在语义分析,$ n $ -gram共现和BLEU之类的不同技术来自动评估摘要。但是,这些技术无法实现良好的性能。在本文中,我们提出了一种集成方法,该方法集成了两种最有效的摘要评估技术:LSA和n-gram共现,以提高自动摘要评估的准确性。所提出的集成方法的性能表明,与其他现有技术相比,该方法能够实现高精度并显着提高性能。

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