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Efficient text summarization method for blind people using text mining techniques

机译:盲人使用文本挖掘技术的高效文本摘要方法

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摘要

Owing to the phenomenal growth in communication technology, most of us hardly have time to read books. This habit of reading is slowly diminishing because of the busy lives of people. For visually challenged people, the situation is even worse. In order to address this impedes, we develop a better and more accurate methodology than the existing ones. In this work, in order to save the efforts for reading the complete text every time, we modify the Weighted TF_IDF (Term Frequency Inverse Document Frequency) algorithm to summarize books into relevant keywords. Then, we compare the modified algorithm with that of the existing algorithms of TextRank Algorithm, Luhn's Algorithm, LexRank Algorithm, Latent Semantic Analysis(LSA). From the comparative analysis, we find that Weighted TF_IDF is an efficient algorithm to automate text summarization and produce an effective summary which is then converted from text to speech. Thus, the proposed algorithm would highly be useful for blind people.
机译:由于通信技术的现象增长,我们大多数人几乎没有时间阅读书籍。由于人们繁忙的生活,这种阅读的习惯正在慢慢减少。对于视觉上挑战的人,情况甚至更糟糕。为了解决这一阻碍,我们开发比现有的更好更准确的方法。在这项工作中,为了节省每次阅读完整文本的努力,我们修改加权TF_IDF(术语频率逆文档频率)算法将书籍汇总到相关的关键字中。然后,我们将修改的算法与Textrank算法,Luhn算法,lexrank算法,潜在语义分析(LSA)的现有算法进行了比较。从比较分析中,我们发现加权tf_idf是一种有效的算法,可以自动化文本摘要,并生成有效摘要,然后从文本转换为语音。因此,所提出的算法对盲人非常有用。

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