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With the tremendous amount of information available electronically, there is an increasing requirement for automatic text summarization systems. An extractive summarization method is represented. The weight of a Chinese word/phrase is computed based on its frequency, part of speech, position and length. The weight of a Chinese sentence is computed by its content, position, length and cue words in...
In this paper we have addressed the qualitative (human evaluation) and quantitative (ROUGE) evaluation of computer generated summaries of the students' essays. The experimental results show that there is a positive high correlation between ROUGE scores and human assessment of the essays (human assigned marks). We have also found out that human evaluation of the automatic summaries positively correlates...
In order to over the shortcoming of the incomprehensive of summarization, a new lexical-chain-based keywords extraction and automatic summarization algorithm from Chinese texts based on the unknown word recognition using co-occurrence of neighbor words is proposed in this paper, and an algorithm for constructing lexical chains based on Hownet knowledge database is given in the method, lexical chains...
In this paper, experiments have addressed the calculation of inter-annotator inconsistency in selecting the content in both manual and automatic summarization of sample TOEFL essays. A new finding is that the linguistic quality of source essay has a very strong correlation with the degree of disagreement among human assessors to what should be included in a summary. This leads to a fully automated...
Automatic summarization systems often make use of sentence extraction methods to select significant content in texts. This paper presents two-sentence extraction strategies. The first one is based on a semantic analysis using word senses built by means of a network of lexical co-occurrences. The second one uses a combination of semantic and syntactical analysis to extract a set of relevant sentences...
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