使用条件随机字段进行命名实体识别
什么是条件随机场？ 条件随机场究竟如何识别结构化或非结构化文本中的人名、组织或地点等专有名称？
例如：该产品由 StackOverFlow Inc. 订购。
条件随机字段如何将 StackOverFlow Inc. 识别为组织？
What is Conditional Random Field?
How does exactly Conditional Random Field identify proper names as person, organization, or place in a structured or unstructured text?
For example: This product is ordered by StackOverFlow Inc.
What does Conditional Random Field do to identify StackOverFlow Inc. as an organization?
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CRF 是一种判别性批量标记模型，与最大熵马尔可夫模型属于同一系列。
完整的解释有书本那么长。
简短的解释如下：
其中最困难的部分是第 4 步中的特征选择和搜索算法。
A CRF is a discriminative, batch, tagging model, in the same general family as a Maximum Entropy Markov model.
A full explanation is book-length.
A short explanation is as follows:
The hard parts of this are feature selection and the search algorithm in step 4.
很好理解，你必须学习很多东西。
首先
了解马尔可夫和贝叶斯网络的基础知识。
由 daphne coller 在 coursera 提供的在线课程
https://class.coursera.org/pgm/lecture/index
CRF 是一种特殊的马尔可夫网络的类型，我们有观察和隐藏状态。
目标是找到未观测变量的最佳状态分配，也称为 MAP 问题。
为大量概率和优化做好准备。 :-)
Well to understand that you got to study a lot of things.
For start
Understand the basic of markov and bayesian networks.
Online course available in coursera by daphne coller
https://class.coursera.org/pgm/lecture/index
CRF is a special type of markov network where we have observation and hidden states.
The objective is to find the best State Assignment to the unobserved variables also known as MAP problem.
Be Prepared for a lot of probability and Optimization. :-)