词语关系的分类？
我不确定用于单词关系分类的最佳算法是什么。例如，在“黄色太阳”这样的句子中，黄色和太阳之间存在关系。到目前为止，我考虑过的机器学习技术有贝恩斯统计、粗糙集、模糊逻辑、隐马尔可夫模型和人工神经网络。
请问有什么建议吗？
谢谢 ：）
I'm not sure whats the best algorithm to use for the classification of relationships in words. For example in the case of a sentence such as "The yellow sun" there is a relationship between yellow and sun. THe machine learning techniques I have considered so far are Baynesian Statistics, Rough Sets, Fuzzy Logic, Hidden markov model and Artificial Neural Networks.
Any suggestions please?
thank you :)
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听起来好像您正在寻找依赖解析器。这样的解析器将为您提供句子中任何单词与其语义或句法核心之间的关系。
MSTParser 使用在线最大保证金技术，称为 MIRA 对单词之间的关系进行分类。 MaltParser 包执行相同的操作，但使用 SVM 来做出解析决策。这两个系统都是可训练的，并提供相似的分类和附件性能，请参阅此处的表 1。
It kind of sounds like you're looking for a dependency parser. Such a parser will give you the relationship between any word in a sentence and its semantic or syntactic head.
The MSTParser uses an online max-margin technique known as MIRA to classify the relationships between words. The MaltParser package does the same but uses SVMs to make parsing decisions. Both systems are trainable and provide similar classification and attachment performance, see table 1 here.
就像用户 dmcer 指出的那样，依赖解析器将为您提供帮助。您可以阅读大量有关依存分析的文献。 本书和这些讲义是介绍传统方法的良好起点。
链接语法解析器有点像依存解析，使用 Sleator 和 Temperley 的链接语法语法来生成单词到单词的链接。您可以在原始链接语法页面上找到更多信息在最近的 Abiword 页面（Abiword 现在维护实现）。
对于依赖解析的非常规方法，您可以阅读 这篇论文模拟了类似于化学/物理学中亚原子粒子相互作用的词与词关系。
Like the user dmcer pointed out, dependency parsers will help you. There is tons of literature on dependency parsing you can read. This book and these lecture notes are good starting points to introduce the conventional methods.
The Link Grammar Parser which is sorta like dependency parsing uses Sleator and Temperley's Link Grammar syntax for producing word-word linkages. You can find more information on the original Link Grammar page and on the more recent Abiword page (Abiword maintains the implementation now).
For an unconventional approach to dependency parsing, you can read this paper that models word-word relationships analogous to subatomic particle interactions in chemistry/physics.
Stanford Parser 正是您想要的。甚至还有在线演示。这是您的示例的结果。
从您的问题来看，您似乎对类型依赖项感兴趣。
The Stanford Parser does exactly what you want. There's even an online demo. Here's the results for your example.
From your question it sounds like you're interested in the typed dependencies.
好吧，没有人知道语言处理的最佳算法是什么，因为它还没有得到解决。能够理解人类语言就是创造一个完整的人工智能。
然而，当然，已经尝试过处理自然语言，这些可能是此类事情的良好起点：
X-Bar 理论
短语结构规则
诺姆·乔姆斯基做到了在自然语言处理方面有很多工作，所以我建议查找他的一些工作。
Well, no one knows what the best algorithm for language processing is because it hasn't been solved. To be able to understand a human language is to create a full AI.
Hoever, there have, of course, been attempts to process natural languages, and these might be good starting points for this sort of thing:
X-Bar Theory
Phrase Structure Rules
Noam Chomsky did a lot of work on natural language processing, so I'd recommend looking up some of his work.