[12] Li Ning.Parallel improvement of Apriori algorithm based on MapReduce[J].Computer Technology and Development,2017,27(4):64-68. [13] LI B,ZHAO H,LV Z H.Parallel ISODATA clustering of remote sensing images ba
An efficient algorithm will have a very good impact on this real world problem. With these things in the background a new algorithm termed as NGramsSA is proposed in this chapter. Along with the details of this algorithm, its performance details have also been compared against the NGrams ...
Language Identification of Web Pages Based on Improved N-gram Algorithm[J] . Chew, Yew Choong,Mikami, Yoshiki,Nagano, Robin Lee.International Journal of Computer Science Issues (IJCSI) . 2011 (3)Chew Y. Choong, Y.M. Robin Lee Nagano, Language identification of web pages based on improved ...
N-Gram是大词汇连续语音识别中 常用的一种语言模型,对中文而言,我们称之为汉语语言模型(CLM, Chinese Language Model)。汉语语言模型利用上下文中相邻词间的搭配信息,在需要把连续无空格的拼音、笔划,或代表字母或笔划的数字,转换成汉字串(即句子)时,可以 计算出具有最大概率的句子,从而实现到汉字的自动转换,无需...
计时的指数空间开销变为线性的,且与所统计的元数无关。基于这种n2gram的统计,本文还进行 了汉语信息熵的计算及字、词级知识获取的研究。本算法及本文的研究结果已应用于我们研制的 机译系统中。 关键词 n元语法 统计 信息熵 知识获取 Algorithmofn-gramStatisticsforArbitrarynand ...
coherence that would eventually lead the automatically generated texts to be detected by a human reader.This article presents an improved implementation of an algorithm of N-Gram statistic imitation and introduces a new concept of manual edition of the stegotexts generated, based on the idea of ...
使用從文字元件擷取 N-Gram 特徵,將 非結構化文字數據特徵化。 從文字元件擷取 N-Gram 功能的設定 此元件支援使用 n-gram 字典的下列案例: 從任意文字的數據行建立新的 n-gram 字典。 使用現有的一組文字功能 ,將自由文字數據行特徵化。 評分或部署使用 n-gram 的模型。 建立新的 n-gram ...
N-gram Counting,Platform For AI:ngram-count is a critical step in the training process of language models, involving the generation and frequency counting of n-grams. During this process, the algorithm identifies sequences of n...
The algorithm, then, is of order V^3 最终,我们只需要根据式15和16计算s_{k-1}(i) 和L_{k-1}(l, i)。决定下一个要合并的簇的操作时间复杂度为V^2。这样最终算法的时间复杂度为V^3注 对于第k次迭代,当i,j遍历的来确定要合并的簇时,第一次的时间复杂度为V^2,但是后续的s_{k-1},q_{k...
This algorithm reduces the calculation of a normalizing factor drastically, which only requires calculation of probabilities of words that appears in the current context. The experimental result showed that the proposed algorithm was more than 6000 times faster than the naive calculation method.Masaharu ...