PMI对有意义词汇选择的积极影响

A. Toprak, M. Turan
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引用次数: 1

摘要

本研究的目的是为了提高自动创建词典的质量。据我们所知,首次使用PMI (point - twise Mutual Information)来确定文献中的代表性词汇。对先前开发的系统进行了修正,进一步实验PMI对代表词选择的影响。首先,利用亥姆霍兹原理确定种子文件的有意义词;然后,为每个有意义的单词计算PMI值。有意义的词用PMI总值从小到大排序。最后,将前n个有意义的单词添加到字典中,其中n是实验性的。哈希相似度用于衡量字典的性能。PMI增强了所有n值的字典质量。在实验中,对于最佳n值,字典哈希相似度从40.46%增加到68.75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Positive Effect of PMI on the Selection of Meaningful Words
The aim of this study is to enhance the quality of automatic created dictionary. As far as we know, PMI (Pointwise Mutual Information) is the first time applied in order to determine representative words in the literature. A previously developed system is revised to experiment PMI effect on the selection of representative words additionally. Firstly, the meaningful words of the seed document/s are determined by Helmholtz Principle. Then, PMI value is calculated for each of the meaningful words. Meaningful words are sorted by using the total PMI value in decreasing order. Finally, the top n meaningful words are added to the dictionary, where n is experimentally worked. Hash similarity is used to measure the performance of the dictionary. PMI enhances the dictionary quality for all n value. The dictionary hash similarity increases from 40.46% up to 68.75% for the best n value in the experiments.
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