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关于 隐马可夫算法 在分词中的应用 区别
1 **原文 https://baike.baidu.com/item/%E9%9A%90%E9%A9%AC%E5%B0%94%E5%8F%AF%E5%A4%AB%E6%A8%A1%E5%9E%8B/7932524?fr=aladdin
2 隐马尔可夫模型 Hidden Markov Model,HMM 德塔分词没有用到。
3 隐马尔可夫模型 基本理论 德塔分词 全部没有用到 如 概率集,随机关联,隐藏参数等
4 隐马尔可夫模型 基本算法 德塔分词 全部没有用到 如 前向算法 Viterbi算法 Baum-Welch算法
5 隐马尔可夫模型 模型表达 德塔分词 全部没有用到 如 隐含观测 概率矩阵
搜索了下当前的隐马可夫分词的算法模型,发现结巴分词出现有概率集和贝叶斯核,大家可以阅读区别下。结巴分词也是源码开源。
作者函数中有一个 命名为HMMnode 动机是2个
1 2009年9月在上海 做了基于lucene的应用开发,当时看不到lucene底层代码,百度搜索上页页都是前序 因马科夫 这些词汇 洗脑。以为从左到右的节点分词模式就是 因马科夫 分词法。
2 作者的德塔分词,也是将字符串进行从左到右按中文语法主谓宾句型 词性搭配来 严谨的固定的准确分词,不存在概率集和隐藏数据,因为从左到右,就大脑马上想到隐马可夫这个词汇。 其实无关,于是感谢下。
关于从左到右,不仅隐马可夫,其实有很多理解力的**都是这个方式,如冯诺依曼 从左到右,从上到下。 如cnn卷积移动方式,从左到右。就连人类阅读,书写作业都是从左到右, 当然,书法毛笔字现在 有从右到左。不多解释了。
刚搜了下百科,前序理解力 严谨定义属于 《排队论》范畴。运筹学的数学分支,应用数学学科。 https://baike.baidu.com/item/%E6%8E%92%E9%98%9F%E8%AE%BA/938889
https://baike.baidu.com/item/%E9%A9%AC%E5%B0%94%E5%8F%AF%E5%A4%AB%E9%93%BE
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